A good place to look for changes. Often I'll add changes here but don't always get to it in the documentation for awhile. They are ordered from newest to oldest.
Jeff Laake
Version 2.0.9 (1 Dec 2011)
Patch was made to make.mark.model to fix bug in
PIM creation for a multi-session model and there was just 1 session. Thanks to Erin Roche for helping to
identify this bug.
Patch was made to make.mark.model to fix bug in
handling of mlogits for pi and Omega parameters with more than one group. These parameters were introduced
with the RDMSMisClass and other new models that were recently added.
Additional changes were made to export.MARK to re-fix changes for robust and nest survival
model export to MARK.
A function mark.wrapper.parallel written by Eldar Rakhimberdiev provides a parallel processing
version of mark.wrapper. See the example in the help for the function. The parallel version is functionally the same
and can be used in place of mark.wrapper to run sequentially or in parallel. It does not include the run argument
however.
A bug was fixed in get.real which caused an R error for a triangular PIM that had only a single entry.
Thanks to Amanda Goldberg for discovering and reporting this error.
Version 2.0.8 (7 Oct 2011)
Both setup.model
and setup.parameters were re-written to use data files
models.txt and parameters.txt to define models and parameters which should
make it easier to add new models. The latter function is now much simpler
and smaller.
Model RDOccupEG now allows sharing Epsilon and Gamma
parameters. Epsilon is the dominant parameter which gets the share=TRUE
argument. See RDOccupancy for an example. Thanks to Jake Ivan
for an example of what was needed.
To avoid confusion, the arguments
component and component.name were removed from the parameter
specification because these have not been required since v1.3 when full
support for individual covariates were included. Likewise the argument
covariates in mark and make.mark.model
was removed because it was only needed to support the component approach.
export.MARK was modified so that if all individual covariates
are output, it excludes factor covariates.
Many more models were added to those supported in RMark. Now 92 of the 137 models in MARK are supported. See MarkModels.pdf in the RMark directory of your R library to see which models are supported (in red). Most of the remaining unsupported models are versions with mis-identification error and they are not shown in MarkModels.pdf.
Previously RMark stored the input file in a temporary file Markxxx.tmp. Using a common filename caused problems when more than one model were spawned to different CPUs, so now it uses a random temporary file name. It also no longer uses common file markxxx.vcv. Thanks to Glenn Stauffer for testing these changes.
Sessions are now labelled using value of session time rather than numerically from 1 to largest session number in robust designs. Thanks to Tommy Garrison for this suggestion.
A bug was fixed in get.real which caused incorrect assignments of fixed
parameter values in the unusual case where a fixed parameter had a non-zero design matrix row.
mark.wrapper was modified so it returns a list of the models that were
constructed if run==FALSE. Thanks to Eldar Rakhimberdiev for the suggestion and code.
Code was added to extract.mark.output to extract deviance degrees of freedom. Thanks
again to Eldar for contributing this code.
A bug was fixed in make.mark.model that prevented use of sin link on within session parameters
in a robust design model. Thanks to Tommy Garrison for reporting this bug.
A bug was fixed in make.mark.model which prevented the use of time varying covariates
with shared parameters. Thanks to Andre Breton for reporting this bug.
simplify argument was removed from functions because I have not found a reason not to simplify and I have not been testing code with simplify=FALSE.
Version 2.0.7 (25 August 2011)
Change to
make.mark.model to fix bug in which mlogits were incorrectly
assigned in ORDMS model when both Psi and pent used mlogit links. Thanks to
Glenn Stauffer for identifying and tracking down this error.
Fixed
export.chdata and export.MARK so Nest survival
models can be exported. Also changed default of argument ind.covariates to
"all" which will use all individual covariates in the data in the file sent
to MARK. Thanks to Jay Rotella for his help.
Made change to
process.data and mark to include a new argument
reverse, which if set to TRUE with model="Multistratum" will reverse the
timing of transition and survival. See mstrata for an example
of a reverse multistratum model.
Made change to
make.design.data to allow for zero time intervals in
non-robust design model. This was needed to allow use of the reverse time
structure in multi-state models. In addition, for the reverse multistate
model the function now adds an occasion (occ) field to the design data
because the time field will be constant when with a 0 time interval. The
row names of the design matrix and real parameters was extended for this
model to include occasion (o) and occasion cohort (oc) to create unique
labels because cohort and time are not unique with 0 time intervals.
Version 2.0.6 (1 July 2011)
Change to MR resight examples so the output does not appear in notepad which was causing problem with check on CRAN submission
Version 2.0.5 (29 June 2011)
Order of
arguments for model.average.marklist were switched incorrectly
such that ... was the second argument. This has been fixed to the original
format where ... is at the end. This resulted in the value of any arguments
other than the first to be ignored unless specifically named e.g.,
parameter="Phi". Thanks to Rod Towell for reporting this error.
Additional changes were made to .First.lib to 1) examine any MarkPath setting, 2) look in C:/program files/mark or c:/program files (x86)/mark, 3) or to search the path. If MARK executable cannot be found in any of those ways then a warning is issued that the user needs to set MarkPath to the path specification for the location of the MARK executable. Thanks to Bryan Wright for help with tracking down a bug.
A bug in
add.design.data was fixed where the function gave incorrect
results in pim.type was anything other than "all". Thanks to Jeff Hostetler
for reporting this error.
The mark-resight models PoissonMR,
LogitNormalMR, and IELogitNormalMR were added. This required some changes
to make.mark.model,make.design.data and
compute.design.data and the addition of an argument
counts to process.data to provide mark-resight count
data that are not in the capture history format. The format for
counts is a named list of vectors (one group) or matrices (each group
is a row) where the names of the list elements are specific to the model.
Currently there is no checking to make sure these are named correctly. Some
of these models are very sensitive to starting values; thus the use of
initial values in the examples. Thanks to Brett McClintock for his help
incorporating these models.
Version 2.0.4 (1 June 2011)
Change made to .First.lib to check for availability of mark software that depends on operating system. It now provides a warning rather than stopping package attachment. This allows the user to set MarkPath to some location outside of default location Program Files or Program Files (x86) without changing path which requires administrator privilege on Windows.
Change made to run.mark.model to use shQuote because link to
mark.exe was not working in some cases.
Version 2.0.3 (17 May 2011)
Now requires R 2.13 to use path.package function
Change made to .First.lib to check for availability of mark software that depends on operating system.
Version 2.0.2 (16 May 2011)
MarkPath no longer needs to be set if mark.exe is no longer in the default location (c:/Program Files/mark) but is specified in the path. The code now uses the R function Sys.which to find the correct location for mark.exe, if it is contained in the Path.
Code for crm models was removed from RMark and moved to a different R package called marked that is under-development. This removes the FORTRAN code and accompanying dll and some functions and help files that were extraneous to RMark capabilities. There is still some code in some functions for crm that could be removed at some point. None of this matters to those who use RMark for its original purpose as an interface to mark.exe.
Many superficial changes were made to code so it could be posted on CRAN. Three changes that may be noticed by users involved renaming deriv.inverse.link, summary.ch and merge.design.covariates to deriv_inverse.link, summary_ch, and merge_design.covariates. These names conflicted with the generic functions deriv, summary and merge. It is only the last 2 that you may have in your scripts and you will have to rename them. The deprecated function merge.occasion.data was removed. Sorry for any inconvenience.
The dependency on Hmisc for the examples was removed by replacing errbar with plotCI.
Version 2.0.1 (21 Feb 2011)
Made a change to
run.mark.model to handle output filenames that exceeded
mark9999.
Added an argument prefix in mark,
run.mark.model and cleanup. Like other
parameters for mark, it can also be used in
mark.wrapper as one of the ... arguments. Previously the mark
files have always been named "marknnn.*". By specifying prefix you
can now create sets of models with different prefixes. For example,
prefix="cu" would result in cu001.*(cu001.out, cu001.inp, etc),
cu002.* etc. This provides the ability to name files to do things like
naming them based on the species being analyzed. In general, there is no
need to work with these files directly because the filename.* is stored with
each mark object and the various R functions use that link to provide
the information from the files. If you use prefixes other than "mark",
you'll need to call call cleanup with each prefix to remove
unused files. See run.mark.model for an example that shows
use of the prefix argument to split the dipper data into separate analyses
for each sex. Note that use of prefix was not mandatory here to separate
the analyses but it provided a useful example.
Additional usefulness
has been coded for argument initial for assigning initial values to
beta parameters. Previously, the options were either a vector of the same
length as the new model to be run or a previously run model in a mark
object from which equivalent betas are extracted based on their names in the
design matrix. Now if the vector contains names for the elements they will
be matched with the new model like with the model option for initial. If
any betas in the new model are not matched, they are assigned 0 as their
initial value, so the length of the initial vector no longer needs to
match the number of parameters in the new model as long as the elements are
named. The names can be retrieved either from the column names of the design
matrix or from rownames(x$results$beta) where x is the name of
the mark object.
Using the feature above, I added a new
argument use.initial to mark.wrapper. If
use.initial=TRUE, prior to running a model it looks for the first
model that has already been run (if any) for each parameter formula and
constructs an initial vector from that previous run. For example, if
you provided 5 models for p and 3 for Phi in a CJS model, as soon as the
first model for p is run, in the subsequent 2 models with different Phi
models, the initial values for p are assigned based on the run with the
first Phi model. At the outset this seemed like a good idea to speed up
execution times, but from the one set of examples I ran where several
parameters were at boundaries, the results were discouraging because the
models converged to a sub-optimal likelihood value than the runs using the
default initial values. I've left this option in but set its default value
to FALSE.
A possibly more useful argument and feature was added to
mark.wrapper in the argument initial. Previously, you
could use initial=model and it would use the estimates from that
model to assign initial values for any model in the set defined in
mark.wrapper. Now I've defined initial as a specific
argument and it can be used as above but you can also use it to specify a
marklist of previously run models. When you do that, the code will
lookup each new model to be run in the set of models specified by
initial and if it finds one with the matching name then it will use
the estimates for any matching parameters as initial values in the same way
as initial=model does. The model name is based on concatenating the
names of each of the parameter specification objects. To make this useful,
you'll want to adapt to an approach that I've started to use of naming the
objects something like p.1,p.2 etc rather than naming them something like
p.dot, p.time as done in many of the examples. I've found that using
numeric approach is much less typing and cumbersome rather than trying to
reflect the formula in the name. By default, the formula is shown in the
model selection results table, so it was a bit redundant. Now where I see
this being the most benefit. Individual covariate models tend to run rather
slowly. So one approach is to run the sequence of models (eg results stored
in initial_marklist), including the set of formulas with all of the
variables other than individual covariates. Then run another set with the
same numbering scheme, but adding the individual covariates to the formula
and using initial=initial_marklist That will work if each parameter
specification has the same name (eg., p.1=list(formula=~time) and then
p.1=list(formula=~time+an_indiv_covariate)). All of the initial values will
be assigned for the previous run except for any added parameters (eg.
an_indiv_covariate) which will start with a 0 initial value.
I added a
new function search.output.files to the set of utility
functions. This can be useful to search all of the output files in a
marklist for a specific string like "numerical convergence suspect"
or just "WARNING". The function returns the model numbers in the
marklist that contain that string in the output file.
Further
changes were needed to popan.derived to handle data that are
summarized (i.e. frequency of capture history >1). Thanks to Carl Schwarz
for reporting and finding the change needed.
A bug was fixed in
create.dm was fixed so it would return a matrix instead of a vector
with the formula ~1
Version 2.0.0 (14 Jan 2011)
The packages msm, Hmisc, nlme, plotrix are now explicitly required to install RMark. These were used in examples or for specialty functions, but to avoid problems these must be installed as well.
Added example for "CRDMS"
model that was created by Andrew Paul. See crdms.
Change was made for gamma link in v1.9.3 was only made to Pradel model and not Pradsen like it stated. Both now correctly use the logit link as the default for gamma. Thanks to Gina Barton for bringing this to my attention.
Change was made in make.mark.model that prevented use of
groups with Nest survival models. Thanks to Jeff Warren for bringing this
to my attention.
Change was made in make.design.data
because re-ordering of parameters caused issues with the CRDMS model because
the subtract.stratum were not being set for Psi.
Version 1.9.9 (2 Nov 2010)
This version was built with R 2.12 and will not work with earlier versions of R. It contains both 32 and 64 bit versions and R will automatically ascertain which to use.
Parameter
ordering for some models (RDHet, RDFullHet, RDHHet, RDHFHet, OccupHet,
RDOccupHetPE, RDOccupHetPG, RDOccupHetEG, MSOccupancy, ORDMS, and CRDMS) had
to be changed such that the models could be imported into the MARK
interface. This change can influence any code you have written for those
models if you specified parameter indices because the ordering of the
parameters were changed. For example, see change in example for
RDOccupancy to use indices=c(1) from c(10). Thanks to Gary
White for helping me work this out.
Modified code in
extract.mark.output to handle cases with more than 9999 real
parameters because MARK outputs **** when it exceeds 9999.
Version 1.9.8 (15 Sept 2010)
Added model="CRDMS" with parameters S,
Psi, N, p, and c for closed robust design multi-state models
Patched
popan.derived which produced incorrect abundance estimates
with unequal time intervals. Thanks to Andy Paul for finding this error and
testing for me.
Patched export.MARK which failed for
robust design models. Thanks to Dave Hewitt and Gary White for discovering
and isolating the problem.
Version 1.9.7 (14 April 2010)
Added model="Brownie" with parameters S and f which is the Brownie et
al. parameterization of the recovery model. "Recovery only" (in RMark)
model="Recovery" which is also encounter type "dead" in MARK uses the
Seber parameterization with parameters S and r which is also used in the
models for live and dead encounter models.
Added
model="MSLiveDead" with parameters S, r, Psi and p. It is the
multistate version of the Burnham model in which F=1.
Added
compute.Sn to utility functions for computation of natural
survival from total survival when all harvest is reported. Patched
nat.surv which was incorrectly rejecting based on model type.
Added var.components.reml to provide an alternate
variance components estimation using REML or maximum likelihood. It allows a
random component that is not iid which is all that
var.components can do.
Replaced all T/F values with TRUE/FALSE to avoid conflicts with objects named TRUE or FALSE.
Version 1.9.6 (1 February 2010)
Writing the
popan.derived function has led me down all sorts of paths. I
had to make one small change to this function to handle externally saved
models. However, various changes listed below were brought on by using this
function with a relatively large POPAN model.
Most importantly I
discovered an error in computations of real parameters with an mlogit link
in which some of the real parameters involved in the mlogit link were fixed.
This is NOT a problem if you simply used the real parameter values extracted
from MARK; however, if you were using either compute.real
(model.average uses this function) or covariate.predictions to
compute those real parameters (with an mlogit link) then they may be
incorrect. This would have been apparent because their value would have
changed relative to the original values extracted from the MARK output.
Correcting this error involved changes in compute.real,
convert.link.to.real and covariate.predictions
to correct the real parameter estimates and their standard errors. I've not
found it in the MARK documentation but deduced that if you use the mlogit
link and fix real parameters it uses those fixed real parameter values in
the calculation. A simple example will make it clear. Consider pent for 5
occasions where the first is computed by subtraction and you then have 4
real parameters. Let's assume that the 3rd and fourth parameters were fixed
to 0. Then the real parameters are calculated as follows:
pent2=exp(beta2)/(1+ exp(beta2)+exp(beta3)+exp(0)+exp(0)),
pent3=exp(beta3)/(1+ exp(beta2)+exp(beta3)+exp(0)+exp(0)), pent4=0, pent5=0
and pent1=1-pent2-pent3-0-0 (in this case). Obviously you would not want to
fix any real parameters to be >1, <0 or to have the sum to be <0 or >1.
This structure also had implications on how the standard error was
calculated.
In addition the coding was made more efficient in
covariate.predictions for the case where
data(index=somevector) is used without any data entries for covariate
values in the design matrix. While the task performed with that use of the
function could be done with compute.real, it is useful to have
the capability in covariate.predictions as well because it
will then model average over the listed set of parameters. The previous
approach to coding was inefficient and led to very large matrices that were
unnecessary and could cause failure with insufficient memory for large
analyses.
Calculation of NGross was added to
popan.derived and logical arguments N and NGross
were added to control what was computed in the call. In addition, argument
drop was added which is passed to covariate.predictions
to control whether models are dropped when variance of betas are not all
positive.
var.components was modified to use qr matrix
inversion. The returned value for beta is now a dataframe that includes the
std errors which are extracted from the vcv matrix. Also, if the design
matrix only uses a portion of the vcv matrix, the appropriate rows and
columns are now extracted. Prior to this change, the standard errors would
have been unreliable if the design matrix didn't use the entire set of
thetas and vcv matrix.
Version 1.9.5 (4 December 2009)
A
bug in covariate.predictions was fixed that would assign fixed
values incorrectly if the parameter indices were specified in anything but
ascending order. The error would have been obvious to anyone that may have
encountered it because estimated parameters would likely have been assigned
a fixed value. In most cases indices would be passed in order if they were
selected from the design data unless indices were chosen from more than one
parameter type. I discovered it using the popan.derived
function I added in v1.9.4 because it requests indices for multiple
parameters in a single function call.
Version 1.9.4 (6 November 2009)
Note that this version was built with R 2.10 which no longer supports compiled help files (chtml). If you were using compiled help files to get help with RMark, you'll need to switch to regular html files by using options(help_type="html") in R. You can put this command in your RProfile.site file so it is set up that way each time you start R. The functionality is the same but it is not as pretty. You can find the index (what used to be in a window on the left) as a link at the bottom of each help page.
Changed export.MARK so it will not allow
selection of a project name that would over-write an existing .inp file.
Added the function popan.derived which for POPAN models
computes derived abundance estimates by group and occasion and sum of group
abundances for each occasion. For some reason RMark is unable to extract all
of the derived parameters from the MARK binary file for POPAN models. This
function provides the derived abundance estimates and their var-cov matrix
and adds the abundance estimate sum across groups for each occasion which is
not provided by MARK. Note that by default confidence intervals are based on
a normal distribution to match the output of MARK, but if you want
log-normal intervals use normal=FALSE.
The
model.average.list and model.average.marklist
functions were modified to use revised estimator for the unconditional
standard error (eq 6.12 of Burnham and Anderson (2002)) which is now the
default in MARK. To use eq 4.9 (the prior formula) set the argument
revised=FALSE.
Fixed bug in model.average.list
which in some cases failed when the list of var-cov matrices were specified.
Code in model.average.marklist was changed to set
standard error to 0 if the variance is negative. The same is done in the
var-cov matrix for the variance and any corresponding covariances. The
results from RMark will now match the model average results from MARK for
this case. It is not entirely clear that this is the best approach when
ill-fitted models are included.
Changed code in cleanup
to handle case in which a model did not run.
Changed use of
grep and regexpr in convert.inp and
extract.mark.output to accomodate change in R.2.10. The code
should work in earlier versions of R but if not update to R2.10.
Created a function adjust.value and kept special case of
adjust.chat. For any field other than chat it will adjust the
value in model$results. As an example, to adjust the effective
sample size (ESS) use model.list=adjust.value("n",value,model.list)
where value is replaced with the ESS you want to use. As part of the change
model.table was changed to recompute AICc.
Version 1.9.3 (24 September 2009)
Default link function for Gamma in the Pradel seniority model had been incorrectly set to log and has now been changed to logit to restrict it to be a probability.
A bug was fixed
in compute.real and covariate.predictions in
which confidence intervals were being incorrectly scaled by c (chat
adjustment) instead of sqrt(c). The reported standard errors were correctly
using sqrt(c) and only the confidence intervals for the real predictions
were too large. Simply re-running the prediction computations for a model
will provide the correct results. There is no reason to re-run the models.
Also this in no way affects model selection.
A related bug was fixed
in compute.real and covariate.predictions which
created invalid confidence intervals for real parameters if a probability
link other than logit was used and a single type of link was used for all
real parameters (e.g., sin).
Version 1.9.2 (10 August 2009)
Added the function export.MARK which creates a .Rinp,
.inp and optionally renames one or more output files for import to MARK.
The July 2009 version of MARK now contains a File/RMARK Import menu item
which will automatically create the MARK project using the information in
these files. This prevents problems that have been encountered in creating
MARK projects with RMark output because the data/group structures are setup
exactly in MARK as they were in RMark. See export.MARK for an
example and instructions.
Fixed a problem in
make.design.data which prevented use of remove.unused
with unequal time intervals and more than one group.
At least one person has encountered a problem with a very large number of parameters in which RMark created the input file with PIMs written in exponential notation for the larger indices. MARK will not accept that format and it will fail. The solution to this is to set the R option scipen to a positive number. Start with options(scipen=1) and increase if necessary.
Version 1.9.1 (2 June 2009)
Fixed a problem make.design.data
which was not using begin.time to label the session values
Made
a change in export.chdata like the change in
make.mark.model to accomodate change with release of version
R2.9.0.
Made a change in process.data so that
strata.labels can be specified for Multistrata designs like with
ORDMS so an unobserved strata can be included.
A warning was added to
the help file for export.chdata and export.model
so it is clear that the MARK database must be created correctly and with the
.inp file created by export.chdata from the processed data
that was used to create the models that are being exported. This is to
ensure that the group structure is setup such that the assumed model
structure for groups matches the model structure setup in the .inp file.
Version 1.9.0 (30 April 2009)
Fixed a bug in
summary.mark which occasionally produced erroneous results
with showall=FALSE.
Made a change in
make.mark.model to accomodate change with release of version
R2.9.0.
RMark now requires R version 2.8.1 or higher.
Version 1.8.9 (9 March 2009)
Changed model.average.marklist
and covariate.predictions to set NaN or Inf results in v-c
matrix to 0 to cope with poorly determined models. Also, for each function
the dropping of models is now restricted to cases in which there are
negative variances for the betas being used in the averaged parameter
estimates. Unused betas are ignored. For example, if
model.average is called with parameter="Phi", then the
model will only be dropped if there is a negative variance for one of the
betas associated with "Phi".
In var.components the
tolerance value (tol) in the call to uniroot was reduced to
1e-15 which should provide better estimates of the process variance when it
is small. Previously a process variance less than 1e-5 would be treated as
0.
Made changes to cleanup, coef.mark, and
make.mark.model to accomodate externally saved model objects
(external=TRUE).
Version 1.8.8 (5 December 2008)
An
error was fixed in make.time.factor which created incorrect
assignments when only some of the time dependent variables contained a "."
for occasions with no data.
Patched compute.design.data
which was not creating the design data in the same order as the PIM
construction for the newly added ORDMS model.
Generalized
section of code in make.mark.model to handle mlogit
structure for ORDMS model.
Fixed a bug in
process.data in which the initial ages were not correctly
assigned in some situations with multiple grouping variables. Note that it
is always a good idea to examine the design data after it is created to make
sure it is structured properly because it relates the data and model
structure via the grouping variables and the pre-defined variables (ie age,
time etc), While I've done a lot of testing, I have certainly not tried
every possible example and there is always the potential for an error to
occur in a circumstance that I've not encountered.
Version 1.8.7 (13 November 2008)
An argument common.zero was added to
function make.design.data and
compute.design.data. It can be set to TRUE to make the
Time variable have a common time origin of begin.time which is
useful for shared parameters like p and c in closed capture
and similar models.
The function read.mark.binary was
patched to work with the newer versions of MARK.EXE since 1 Oct 2008.
The model type ORDMS for open robust design multi-state models was
added. An example data set will be added at a later date after further
testing has been completed.
Some patches were made to fix some aspects
of profile intervals and to fix adjustment by chat in
summary.mark when showall=F. The notation for profile
intervals is now included in the field model$results$real$note where
model is the name of a mark model. Previously an incomplete notation
was kept in model$results$real$fixed but that field is now used
exclusively to denote fixed parameters. It is important to realize that
profile intervals computed by MARK are only found in
model$results$real$note and are not changed by a chat
adjustment unless the model is re-run. None of the intervals computed by
RMark and displayed by summary.mark are profile
intervals.
Version 1.8.6 (28 October 2008)
A bug in an
error message for initial.ages in process.data was
fixed.
A new function var.components was added to
provide variance components capability as in the MARK interface except that
shrinkage estimators are not computed currently.
Fixed parameter
values are now being reported correctly by
covariate.predictions. Also over-dispersion (c>1) was not
being included in the variances for parameters except those using the mlogit
link.
Some utility functions were added including
pop.est,nat.surv, and
extract.indices.
The function
model.average has been changed to a generic function.
Currently it supports 2 classes: 1) list, and 2) marklist. The latter was
the original model.average which has been renamed
model.average.marklist and the first argument has been renamed
x instead of model.list to match the standard generic function
approach. The previous syntax model.average(...) will work as long
as the usage does not name the first agument as in the example
model.average(model.list=dipper.results,...). The list formulation
(model.average.list) was created to enable a generic model
averaging of estimates instead of just real parameter estimates from a
mark model. It could be used with any set of estimates, model
weights and estimates of precision.
A change is needed to
read.mark.binary to accomodate the change to mark.exe with the
version dated 1 Oct 2008. Some data types (notably Nest survival) may not
work with the new version of mark.exe. Working with Gary to make the patch.
If you need an older version of mark.exe contact me.
Version 1.8.5 (8 October 2008)
A bug in process.data was fixed
that prevented use of a dataframe contained in a list while using the
groups argument.
Profile intervals on the real parameters can
now be obtained from MARK using the arguments profile.int and
optionally chat in mark. The argument
profile.int can be set to TRUE and a profile interval will be
constructed for all real parameters, or a vector of parameter indices can be
specified to restrict the profiling to certain parameters. The value
specified by chat is passed to MARK for over-dispersion.
References to cjs, js etc have been removed from here because this code was removed 5/11/11.
Yet another fix to summary.ch which
gave incorrect results for the number recaptured at least once when
marray=F and the data contained non-unity values for freq.
Version 1.8.4 (29 August 2008)
A generic function
coef.mark was added to extract the table of betas from the
model with the expression coef(model) where model is a
mark model that has been run and contains output. The table includes
standard errors and confidence intervals.
An argument brief was
added to summary.mark. If brief=TRUE the real
parameters are not included in the summary.
References to cjs, js etc have been removed from here because this code was removed 5/11/11.
A
bug in summary.ch was fixed. It would produce erroneous
results when the data contained a non-constant freq field. Results
with the default of freq=1 were fine.
The function
adjust.chat and its help file were changed such that it was
clear that a model.list argument was needed.
Version 1.8.3 (25 July 2008)
For robust design models, an error trap was added to
process.data to make sure that the capture history length
matches the specification for the time.intervals. This error was
already trapped for non-robust models.
Fixed an error in
make.mark.model that prevented interaction model of
session/time-specific individual covariates in a robust design model.
Fixed an error in process.data so that the field freq
is optional for nest survival data sets.
print.mark was
modified to add an argument input which if set to input=TRUE
will have the MARK input file be displayed rather than the output file.
Also, wait=FALSE was set in the system command which means the viewer
window will be opened and you can carry on with R. Before you had to close
the viewer window before proceeding with R.
An example
RDOccupancy provided by Bret Collier was added for the Robust
Occupancy model which shows the use of session and time-varying individual
covariates in a robust design model.
Version 1.8.2 (26 June 2008)
summary.ch was modified to allow missing
cohorts (no captures/recaptures) for an occasion and to fix a bug in which
bygroup=FALSE did not work when groups were defined.
To avoid
running out of memory, an argument external has been added to
collect.models, mark, rerun.mark,
and run.mark.model. As with all arguments of
mark, external can also be set in
mark.wrapper. Likewise, external can also be set in
run.models and it is passed to run.mark.model.
The default is external=FALSE but if it is set to TRUE then
the mark model object is saved in an external file with an extension
.rda and the same base filename as its matching MARK output files.
The mark object in the workspace is a character string which is the name of
the file with the saved image (e.g., "mark001.rda"). If
external=TRUE with mark.wrapper then the resulting
marklist contains a list entry for each mark model which is only the
filename and then the last entry is the model.table. All of the
functions recognize the dual nature of the mark object (i.e., filename or
mark object) in the workspace. So even if the mark object only contains the
filename, functions like print.mark or
summary.mark will work. However, if you have used
external=TRUE and you want to look at part of a mark object without
using one of the functions, then use the function load.model.
Whereas, before you may have typed mymark$results, if you use
external=TRUE, you would replace the above with
load.model(mymark)$results.
Functions store and
restore were created to store externally and
restore models from external storage into the R workspace. They work
on a marklist and are only needed to store externally existing
marklist models or ones originally created with external=FALSE or to
restore if you change your mind and decide to keep them in the R
workspace.
Error in setup for robust design occupancy models with more than 2 primary sessions was fixed. The error resulted in mark.exe crashing.
The concept of time-varying individual covariates has been
expanded to include robust design models which have both primary (session)
and secondary (time) occasion-specific data. For a robust design, a
time-varying individual covariate can be either session-dependent or
session-time dependent. As an example, if there are 3 primary sessions and
each has 4 secondary occasions, then the individual covariates can be named
x1,x2,x3 to be primary session-dependent or named
x11,x12,x13,x14,x21,x22,x23,x24,x31,x32,x33,x34. The value of x can be any
name for the covariate. In the formula only the base name is used (e.g.,
~x) and RMark fills in the individual covariate names that it finds
that match either the session or session-time individual covariates.
Version 1.8.1 (19 May 2008)
Added function
summary.ch to provide summaries of the capture history data
(resighting matrices and m-arrays). It will not work with all types of
models at present. It will work with CJS and Jolly-type models.
Added
argument model.name to model.table to be able to use
alternate names in the model table. It can use either the model name with
each mark object which uses a formula notation (the current approach) or it
can use the name of the R object containing the mark model
(model.name=FALSE). See model.table for an example.
Also, the help file for model.table was updated to reflect the code
changes implemented in version 1.7.3.
Code in
mark.wrapper was modified to output the number of columns and
column names of the design matrix for each model if run=FALSE. This
allows a check of each of the columns included in the model. By reviewing
these you can assess whether the model was constucted as you intended. If
there is any question you can either use model.matrix or
make.mark.model to examine the design matrix more thoroughly.
A bug in the new function merge.design.covariates was
fixed in which merge was sorting the design data which does obvious
bad things. Adding sort=FALSE does not appear to mean that the data
frame is left in its original order. To prevent this, the dataframe is
forced to remain in its original order by adding a sequence field for
re-sorting after the merge.
Version 1.8.0 (8 May 2008)
Fixed a bug in model.average that caused it to fail and issue
an error when any of the models included a time dependent covariate in the
parameter being averaged.
Added merge.design.covariates
which is meant to replace merge.occasion.data. This new function
allows covariates to be assigned by time, time and
group, or just group. It also uses a simplified list of
arguments and works with individual design dataframes rather than the entire
ddl. It uses the R function merge which can be used on its own
to merge design covariates into the design data. You can use
merge directly as this function only checks for some common
mistakes before it calls merge and it handles reassignemnt of row
names in the case were design data have been deleted. An example, where you
might want to use merge instead of this function would be situations
where the design data are not just group, time or group-time specific. For
example, if groups were specified by two different factor variables say
initial age and region and the design covariates were only region-specific.
It would be more efficient to use merge directly rather than this
function which would require an entry for each group which would be each
pairing of inital age and region. If you use merge and you
deleted design data prior to merging, save the row.names, merge and then
reassign the row.names.
An argument run was added to
mark.wrapper. If set to FALSE, then it will run through each
set of models in model.list and try to build each model but does not
attempt to run it. This is useful to check for and fix any errors in the
formula before setting off a large run. If you use run=FALSE do not
include arguments that are meant to be passed to
run.mark.model like adjust.
Version 1.7.9 (7 April 2008)
make.design.data was fixed so that
remove.unused=T will work properly when different begin.time
values are specified for each group.
Version 1.7.8 (12 March 2008)
Changed the default link for N to log in the
setup.parameters for the HetClosed and FullHet.
It was incorrectly set to logit which created incorrect estimates to be
computed in model.average because MARK forces the log link for
N regardless of what is set in the input file.
Version 1.7.7 (6 March 2008)
Supressed warning message that occurred with code to
check the validity of the sin link in make.mark.model.
Fixed a couple of bugs in covariate.predictions that prevented
it from working for some cases after including code for the sin link.
Added function release.gof to construct the RELEASE goodness
of fit test and extract the TEST2 and TEST3 final chi-square, df and
P-values.
Version 1.7.6 (26 Feb 2008)
make.mark.model was modified to change the capitalization of
the link functions and to remove all spaces after "=" in the input file for
mark.exe. These differences were preventing the MARK interface from fully
importing the model. Although the model would be imported and could be run
inside the MARK interface, median c-hat would not run and would give an
error stating "Invalid Link" for any model imported from RMark. Now
transfering a model from RMark to the MARK interface is fully functional (I
hope). If you want to import an output file that was created with a prior
version of RMark without re-running it, use a text editor on the output file
and remove any spaces before and after an = sign. Then change the
capitalization of the links to "Logit", "MLogit", "Log", "LogLog",
"CLogLog", "Identity".
The sin link is now supported if the formula for the parameter generates an identity matrix for the parameter. For example, if you use ~-1+time instead of ~time then the resulting design matrix will be an identity for time. Likewise, for interactions use ~-1+group:time instead of ~group*time. If you select the sin link and the resulting design matrix is not an identity for the parameter, an error will be given and the run will stop.
To match the output from MARK, the confidence intervals for real parameters using any 0-1 link including loglog,cloglog,logit and sin are now computed using the logit transformation. For previous versions this will only affect any results that were using loglog and cloglog. Previously, it was using the chosen link to compute the se and the interval endpoints. The latter is still used for the log and identity links which are not bounded in 0-1.
The model
"Jolly" was added to the supported list of models. Parameters include
Phi,p,Lambda,N. It is not a particularly numerically stable model and often
will not converge. Use of options="SIMANNEAL" in call to mark
is recommended for better convergence. It will take much longer to converge
but is mroe reliable.
Version 1.7.5 (24 Jan 2008)
model.average was modified to ignore any models that did not
run and either had no attached output file or no results.
read.mark.binary and extract.mark.output were
modified to extract and store the real.vcv matrix (var-cov matrix of the
simplified real parameters) in the mark object if realvcv=TRUE. The default
is realvcv=FALSE. This argument has been added to functions
mark, run.mark.model and
rerun.mark.
An argument delete has also been added to
mark and run.mark.model. The default value is
FALSE but if set to TRUE it deletes all output files created by MARK after
extracting the results. This is most useful for simulations that could
easily create thousands of output files and after extracting the results the
model objects are no longer needed. This is just a convenience to replace
the need to call cleanup.
Version 1.7.4 (10 Jan 2008)
A bug in make.mark.model was fixed. It was
preventing creation of individual (site) covariate models for parameters
with only a single parameter (single index) in certain circumstances like
Psi1 in the MSOccupancy model.
The fix to merge.occasion.data
in version 1.7.1 did not work when design data had been deleted. That has
been remedied.
Various functions with some operating specific calls
have been modified so they will work on either Windows or Linux. Thus, the
there is a single file for all source/help for both operating systems in
RMarkSource.zip. It can be downloaded to either Windows or Linux to build
the package. You need to build the package for Linux but not for Windows.
For Windows, you only need RMark.zip which contains the pre-built package
which only needs to be installed. Currently, with Linux the variable
MarkPath is ignored and mark.exe is assumed to be in the path. Also, for
Linux the default for MarkViewer is "pico" (an editor on some Linux
machines). This can be modified in print.mark or by setting
MarkViewer to a different value. The one Linux specific function is
read.mark.binary.linux. The function
extract.mark.output calls either read.mark.binary.linux
or read.mark.binary depending on the operating system. A Linux
version of mark.exe (32 or 64 bit) can be obtained from Evan.
Version 1.7.3 (4 Jan 2008)
In working with the occupancy models, it
became apparent that it would be useful to have a new function called
make.time.factor which creates time-varying dummy variables
from a time-varying factor variable. An example is given using observer
with the occupancy dataset weta from the MacKenzie et al
Occupancy modelling book.
To match the results in the book, I added
arguments use.AIC and use.lnl to function
model.table to construct a results table with AIC rather than
AICc and -2LnL values. The latter is more useful with a mix of models some
using individual covariates and others not.
A modification was made to
make.mark.model with the MSOccupancy model to fix the
name of the added data for parameter p1 when share=TRUE to be
p2. For an example which uses p2 to construct an additive model, see
NicholsMSOccupancy.
Version 1.7.2 (20 Dec 2007)
In changing code for the occupancy models, a brace was misplaced which
prevented the nest survival models from working. This has been fixed. Also,
the example code for mallard and killdeer was
modified to exclude the calls to process the input file. This enables use
of the function example() to run the example code (e.g.
example(mallard)). From now on as I add examples they are being
included in my test set to avoid this type of problem in the future.
Version 1.7.1 (14 Dec 2007)
If you update with this version of RMark make sure to update MARK also, so you get the fixes for some of the occupancy models.
A minor bug was fixed in function
merge.occasion.data that created duplicate row names and prevented
the design data from being used in a model.
Thirteen different
occupancy models were added. Models in the following list use the
designation from MARK: Occupancy, OccupHet, RDOccupEG, RDOccupPE,
RDOccupPG, RDOccupHetEG, RDOccupHetPE, RDOccupHetPG,OccupRNPoisson,
OccupRNNegBin,OccupRPoisson,OccupRNegBin,MSOccupancy. Het
means it uses the Pledger mixture and those with RD are the robust
design models. The 2 letter designations for the RD models are shorthand for
the parameters that are estimated. For EG, Psi, Epsilon, and Gamma
are estimated, for PE gamma is dropped and for PG, Epsilon is
dropped. For the latter 2 models, Psi can be estimated for each primary
occasion. The last 5 models include the Royle/Nichols count (RPoisson) and
presence (RNPoisson) models and the multi-state occupancy model. See
salamander for an example of Occupancy, OccupHet,
Donovan.7 for an example of
OccupRNPoisson,OccupRNNegBin, Donovan.8 for an example
of OccupRPoisson,OccupRNegBin, see RDSalamander for an
example of the robust design models and NicholsMSOccupancy for
an example of MSOccupancy. salamander data.
The
functions create.model.list and mark.wrapper
were modified so that a list of parameters can be used to loop. This is
useful in the situation with shared parameters such as p1 and
p2 in the MSOccupancy model, closed models etc. See
p1.p2.different.dot in NicholsMSOccupancy for an
example. It can also be useful if the model definitions are linked
conceptually (e.g., when one parameter is time dependent, the other should
also be time dependent).
The "." value in an encounter history is now acceptable to RMark and gets passed to MARK for interpretation as a missing value.
print.marklist was fixed to show the model table
properly after a c-hat adjustment was made. The change in the code in
version 1.6.5 to add parameter specific values to the model table had the
side-effect of dropping the model name if c-hat was adjusted.
Version 1.7.0 (7 Nov 2007)
A function
deltamethod.special for computation of delta method variances
of some special functions was added. It uses the function
deltamethod from the package msm. You need to install the
package msm from CRAN to use it.
A more complete example
(mallard) created by Jay Rotella was added for the nest
survival model. His script provides a nice tutorial for RMark and the
utility of R to provide a wide-open capability to calculate/plot etc with
the results. It also demonstrates the advantages of scripting in R to
document your analysis and enable it to be repeated. Before you use his
tutorial you need to install the package plotrix from CRAN. At a later date,
Jay has said he will add some additional examples to demonstrate use of the
deltamethod function to create variances for functions of the results
from MARK.
Various changes were made to help files. A more complete
description of cleanup was given to tie into
mallard example.
Version 1.6.9 (10 Oct 2007)
Nest survival model was added to list of MARK models supported by RMark. See
killdeer for an example. Note that the data structure for
nest models is completely different from the standard capture history so the
functions import.chdata, export.chdata and convert.inp
do not work with nest data structure.
Slight change was made to
run.mark.model and print.markto accomodate
change in R 2.6.0.
Version 1.6.8 (2 Oct 2007)
Changes were
made to merge.occasion.data to enable group and time-specific design
covariates to be added to the design data.
Change was made to
setup.parameters to use a log-link for N in the closed-capture
models. MARK forces that link for N but the change was needed for
model.average which does the inverse-link computation. Note
that the reported N in model.average is actually f0 (number
not seen). To get the correct values for N simply add M_t+1 (unique number
captured) to f0. That is the way MARK computes N. The std error and
confidence interval is on f0 such that the lower ci on N will never be less
than M_t+1.
An error was fixed in the output of
model.average. When you selected a specific parameter, it was
giving a UCL which was a copy from one of the models and not the UCL from
the model averaging. If you didn't specify vcv=T it only showed the
errant UCL and if you did specify vcv=T then it showed the correct
LCL and UCL but then added the errant UCL in a column. This occurred because
it was adding covariate data for the specific parameter and was shifted a
column because of a change in 1.6.1.
Version 1.6.7 (7 Aug 2007)
Changes were made in print.mark,
print.summary.mark and compute.design.data to
acommodate changes in V2.5.1 of R. When upgrading versions of R problems may
occur if RMark was built with an earlier version of R. The version of R
that was used to build RMark is listed on the screen each time it is loaded
with library(RMark) This is RMark 1.6.7 Built: R 2.5.1;
i386-pc-mingw32; 2007-08-07 09:00:33; windows
The help file for
import.chdata was expanded to clarify the differences between
it and convert.inp and the use of the freq field.
Version 1.6.6 (14 May 2007)
Function
make.mark.model was fixed so that the real label indices were
properly written when simplify=FALSE is used.
Function
make.mark.model was also changed to remove the parameter
simplification for mlogit parameters that was added in v1.4.5. I
mistakenly assumed that the mlogit parameters were setup such that
the normalization to sum to 1 was done will all the real parameters in the
set (i.e., all PSI for a single stratum). In fact, the mlogit values
are only specified for the unique real parameters so if there is any
simplification and the sum of the probabilities is close to 1 (excluding
subtraction value) the values will not be properly constrained. For
example, with the mstrata data if the problem was constrained
such that PSI from AtoB was equal to AtoC, it is still necessary to have
these as separate real parameters and constrain them with the design matrix.
As it turns out, with the mstrata example it does not matter
because the problem is such that the sum of Psi for AtoB and AtoC is not
close to 1 (same for other strata) and any link will work. This change will
only be noticeable in situations in which the constraint matters (i.e., the
probability for the subtraction parameter is near 0). The change back to
non-simplification for mlogit parameters may increase execution times
because the design matrix size has been increased. Previous users of the
Multistrata design will see very little difference in there results if they
only used models containing stratum:tostratum because that will create an
all-different PIM within each mlogit set. When I ran the
mstrata examples with this version and compared them to v1.6.5
the results were different but they were differences in the 5th or smaller
decimal point due to differences in numerical optimization.
Version 1.6.5 ( 3 May 2007)
Function model.table was
modified to include parameter formula fields in the model.table
dataframe of a marklist. Previously only the model.name was
included which is a concatenation of the individual parameter formulas. The
additional fields allows extracting the model table results based on one of
the parameter formulas or to create a matrix of model AICc or other values
with rows as one parameter and colums as the other. See
model.table for an example.
Function
process.data was modified such that factor variables used for
grouping retain the ordering of the factor levels in the data file.
Previously they would revert back to default ordering and the re-leveling
would also have to be repeated on the design data also.
An argument
brief was added to mark to control amount of summary
output.
Fixed a bug in get.real that prevented
computation for models without the stored covariate values.
Added code
to make.mark.model that prevents constructing models with
empty rows in the design matrix unless the parameter is fixed. For example,
if you were to try ~-1+Time for the dipper data, it will fail now because
there is no value for the intercept (Time=0).
Function
mark.wrapper outputs the model name to the screen before
running the model which helps associate any error messages to the model if
output=F.
Version 1.6.4 (7 March 2007)
A new
function export.model was created to copy the output files
into the naming convention needed to append them into a MARK .dbf/.fpt
database so they can be used with the MARK interface features. This is
useful to be able to use some of the features not contained in RMark such as
median c-hat and variance component estimation. To create a MARK database,
first use export.chdata to create a .inp file to pass the data
into MARK. Start MARK and use File/New to create a new database. Select
the appropriate Data Type (model in RMark) and fill in the appropriate
values for encounter occasions etc. For the Encounter Histories File Name,
select the file you created with export.chdata. Once you have
created the database in the Program MARK interface, click on the Browse menu
item and then Output/Append and select the output file(s) (i.e those with a
Y.tmp) that you exported with export.model. Note that this
will not work with output files run with versions of RMark prior to this one
because the MARK interface will give a parse error for the design matrix.
To get around