AICcmodavg (version 2.1-1)

xtable: Format Objects to LaTeX or HTML

Description

Functions to format various objects following model selection and multimodel inference to LaTeX or HTML tables. These functions extend the methods from the xtable package (Dahl 2014).

Usage

# S3 method for aictab
xtable(x, caption = NULL, label = NULL, align = NULL, 
        digits = NULL, display = NULL, nice.names = TRUE,
        include.AICc = TRUE, include.LL = TRUE, include.Cum.Wt = FALSE,
        …)
# S3 method for bictab
xtable(x, caption = NULL, label = NULL, align = NULL, 
        digits = NULL, display = NULL, nice.names = TRUE,
        include.BIC = TRUE, include.LL = TRUE, include.Cum.Wt = FALSE,
        …)
# S3 method for boot.wt
xtable(x, caption = NULL, label = NULL, align = NULL,
        digits = NULL, display = NULL, nice.names = TRUE,
        include.AICc = TRUE, include.AICcWt = FALSE, …)
# S3 method for countDist
xtable(x, caption = NULL, label = NULL,
        align = NULL, digits = NULL, display = NULL,
        nice.names = TRUE, table.countDist = "distance", …)
# S3 method for checkParms
xtable(x, caption = NULL, label = NULL,
        align = NULL, digits = NULL, display = NULL,
        nice.names = TRUE, include.variable = TRUE, include.max.se =
        TRUE, include.n.high.se = TRUE, …)
# S3 method for countHist
xtable(x, caption = NULL, label = NULL,
        align = NULL, digits = NULL, display = NULL,
        nice.names = TRUE, table.countHist = "count", …)
# S3 method for detHist
xtable(x, caption = NULL, label = NULL,
        align = NULL, digits = NULL, display = NULL,
        nice.names = TRUE, table.detHist = "freq", …)
# S3 method for dictab
xtable(x, caption = NULL, label = NULL, align = NULL, 
        digits = NULL, display = NULL, nice.names = TRUE,
        include.DIC = TRUE, include.Cum.Wt = FALSE, …)
# S3 method for mb.chisq
xtable(x, caption = NULL, label = NULL, align = NULL,
        digits = NULL, display = NULL, nice.names = TRUE,
        include.detection.histories = TRUE, …)
# S3 method for modavg
xtable(x, caption = NULL, label = NULL, align = NULL,
        digits = NULL, display = NULL, nice.names = TRUE,
        print.table = FALSE, …)
# S3 method for modavgEffect
xtable(x, caption = NULL, label = NULL,
        align = NULL, digits = NULL, display = NULL, nice.names = TRUE, 
        print.table = FALSE, …)
# S3 method for modavgPred
xtable(x, caption = NULL, label = NULL,
        align = NULL, digits = NULL, display = NULL, nice.names = TRUE,  
        …)
# S3 method for modavgShrink
xtable(x, caption = NULL, label = NULL,
        align = NULL, digits = NULL, display = NULL, nice.names = TRUE, 
        print.table = FALSE, …)
# S3 method for multComp
xtable(x, caption = NULL, label = NULL,
        align = NULL, digits = NULL, display = NULL, nice.names = TRUE, 
        print.table = FALSE, …)

Arguments

x

an object of class aictab, bictab, boot.wt, checkParms, countDist, countHist, detHist, dictab, mb.chisq, modavg, modavgEffect, modavgPred, modavgShrink, or multComp.

caption

a character vector of length 1 or 2 storing the caption or title of the table. If the vector is of length 2, the second item is the short caption used when LaTeX generates a list of tables. The default value is NULL and suppresses the caption.

label

a character vector storing the LaTeX label or HTML anchor. The default value is NULL and suppresses the label.

align

a character vector of length equal to the number of columns of the table specifying the alignment of the elements. Note that the rownames are considered as an additional column and require an alignment value.

digits

a numeric vector of length one or equal to the number of columns in the table (including the rownames) specifying the number of digits to display in each column.

display

a character vector of length equal to the number of columns (including the rownames) specifying the format of each column. For example, use s for strings, f for numbers in the regular format, or d for integers. See formatC for additional possible values.

nice.names

logical. If TRUE, column labels are modified to improve their appearance in the table. If FALSE, simpler labels are used, or the ones supplied directly by the user in the object storing the output.

include.AICc

logical. If TRUE, the column containing the information criterion (AIC, AICc, QAIC, or QAICc) of each model is printed in the table. If FALSE, the column is suppressed.

include.BIC

logical. If TRUE, the column containing the information criterion (BIC or QBIC) of each model is printed in the table. If FALSE, the column is suppressed.

include.DIC

logical. If TRUE, the column containing the deviance information criterion (DIC) of each model is printed in the table. If FALSE, the column is suppressed.

include.LL

logical. If TRUE, the column containing the log-likelihood of each model is printed in the table. If FALSE, the column is suppressed.

include.Cum.Wt

logical. If TRUE, the column containing the cumulative Akaike weights is printed in the table. If FALSE, the column is suppressed.

include.AICcWt

logical. If TRUE, the column containing the Akaike weight of each model is printed in the table. If FALSE, the column is suppressed.

include.detection.histories

logical. If TRUE, the column containing detection histories is printed in the table. If FALSE, the column is suppressed.

include.variable

logical. If TRUE, the column containing the variable name is printed in the table. If FALSE, the column is suppressed.

include.max.se

logical. If TRUE, the column containing the maximum SE in the model is printed in the table. If FALSE, the column is suppressed.

include.n.high.se

logical. If TRUE, the column containing the number of SE's greater than the threshold specified by the user is printed in the table. If FALSE, the column is suppressed.

print.table

logical. If TRUE, the model selection table is printed and other sections of the output are suppressed (e.g., model-averaged estimates). If FALSE, the model selection table is suppressed and only the other portion of the output is printed in the table.

table.detHist

character string specifying, either "freq", "prop", or "hist". If table.type = "freq", the function returns a table of frequencies of sites sampled, of sites with at least one detection, and for data with multiple primary periods, the frequencies of sites with observed extinctions and colonizations. If table.type = "prop", the table returns the proportion of sites with at least one detection, and for data with multiple periods, the proportion of sites with observed extinctions and colonizations. If table.type = "hist", the function returns the frequencies of each observed detection history.

table.countDist

character string specifying, either "distance", "count", "freq", or "prop". If table.type = "distance", the function returns a table of counts summarized for each distance class. If table.type = "count", the function returns the table of frequencies of counts observed across sites. If table.type = "freq", the function returns a table of frequencies of sites sampled, of sites with at least one detection, and for data with multiple primary periods, the frequencies of sites with observed extinctions and colonizations. If table.type = "prop", the table returns the proportion of sites with at least one detection, and for data with multiple periods, the proportion of sites with observed extinctions and colonizations.

table.countHist

character string specifying, either "count", "freq", "prop", or "hist". If table.type = "count", the function returns the table of frequencies of counts observed across sites. If table.type = "freq", the function returns a table of frequencies of sites sampled, of sites with at least one detection, and for data with multiple primary periods, the frequencies of sites with observed extinctions and colonizations. If table.type = "prop", the table returns the proportion of sites with at least one detection, and for data with multiple periods, the proportion of sites with observed extinctions and colonizations. If table.type = "hist", the function returns the frequencies of each observed count history.

…

additional arguments passed to the function.

Details

xtable creates an object of the xtable class inheriting from the data.frame class. This object can then be used with print.xtable for added flexibility such as suppressing row names, modifying caption placement, and format tables in LaTeX or HTML format.

References

Dahl, D. B. (2014) xtable: Export tables to LaTeX or HTML. R package version 1.7-3. https://cran.r-project.org/package=xtable.

See Also

aictab, boot.wt, dictab, formatC, mb.chisq, modavg, modavgEffect, modavgPred, modavgShrink, multComp, xtable, print.xtable

Examples

# NOT RUN {
if(require(xtable)) {
##model selection example
data(dry.frog)
##setup candidate models
Cand.models <- list( )
Cand.models[[1]] <- lm(log_Mass_lost ~ Shade + Substrate +
                       cent_Initial_mass + Initial_mass2,
                       data = dry.frog)
Cand.models[[2]] <- lm(log_Mass_lost ~ Shade + Substrate +
                       cent_Initial_mass + Initial_mass2 +
                       Shade:Substrate, data = dry.frog)
Cand.models[[3]] <- lm(log_Mass_lost ~ cent_Initial_mass +
                       Initial_mass2, data = dry.frog)
Model.names <- c("additive", "interaction", "no shade")

##model selection table - AICc
out <- aictab(cand.set = Cand.models, modnames = Model.names)

xtable(out)
##exclude AICc and LL
xtable(out, include.AICc = FALSE, include.LL = FALSE)
##remove row names and add caption
print(xtable(out, caption = "Model selection based on AICc"),
      include.rownames = FALSE, caption.placement = "top")


##model selection table - BIC
out2 <- bictab(cand.set = Cand.models, modnames = Model.names)

xtable(out2)
##exclude AICc and LL
xtable(out2, include.BIC = FALSE, include.LL = FALSE)
##remove row names and add caption
print(xtable(out2, caption = "Model selection based on BIC"),
      include.rownames = FALSE, caption.placement = "top")


##model-averaged estimate of Initial_mass2
mavg.mass <- modavg(cand.set = Cand.models, parm = "Initial_mass2",
                    modnames = Model.names)
#model-averaged estimate
xtable(mavg.mass, print.table = FALSE)
#table with contribution of each model
xtable(mavg.mass, print.table = TRUE)  


##model-averaged predictions for first 10 observations
preds <- modavgPred(cand.set = Cand.models, modnames = Model.names,
                    newdata = dry.frog[1:10, ])
xtable(preds)
}


##example of diagnostics
# }
# NOT RUN {
if(require(unmarked)){
##distance sampling example from ?distsamp
data(linetran)
ltUMF <- with(linetran, {
              unmarkedFrameDS(y = cbind(dc1, dc2, dc3, dc4),
              siteCovs = data.frame(Length, area, habitat),
              dist.breaks = c(0, 5, 10, 15, 20),
              tlength = linetran$Length * 1000, survey = "line",
              unitsIn = "m")
              })

##summarize counts across distance classes
xtable(countDist(ltUMF), table.countDist = "distance")
##summarize counts across all sites
xtable(countDist(ltUMF), table.countDist = "count")

##Half-normal detection function
fm1 <- distsamp(~ 1 ~ 1, ltUMF)
##determine parameters with highest SE's
xtable(checkParms(fm1))
}
# }