varComprob()
and AuxiliariesTuning Parameters for varComprob()
which performs S, composite S and
Tau estimators for variance component models.
varComprob.control(init = NULL, lower = 0, upper = Inf, epsilon = 0.001,
tuning.chi = NULL, bb = 0.5, tuning.psi = NULL,
arp.chi = 0.1, arp.psi = NULL, max.it = 100,
rel.tol.beta = 1e-06, rel.tol.gamma = 1e-05, rel.tol.scale = 1e-05,
trace.lev = 0,
method = c("compositeTau", "compositeS", "compositeMM",
"Tau", "S", "MM"),
psi = c("optimal", "bisquare", "rocke"),
beta.univ = FALSE, gamma.univ = FALSE,
fixed.init = c("lmrob.S", "lmRob"),
cov.init = c("TSGS", "2SGS", "covOGK"),
cov = TRUE, ...)
returns a named 'list' with over twenty components, corresponding to the arguments.
A list with initial values. The only components used are
beta
, gamma
, eta0
, scales
(in case of
composite methods), scale
(in case of classic methods) and
Sigma
. If one of the components is empty a suitable automatic
initial values is calculated.
A numeric vector with length equals to gamma
. This
parameter is passed to the optim
function.
A numeric vector with length equals to gamma
. This
parameter is passed to the optim
function.
A positive numeric scalar. This value is set to the non
negative elements of gamma
(checked by lower
) when the
automatic initial values are negative.
tuning constant vector for the rho_1 function. If
NULL
, as by default, this is set, depending on "psi" (for now only
"bisquare" and "optimal"), to a suitable value.
expected value under the normal model of the rho function
with tuning constant equal to tuning.chi
.
tuning constant vector for the rho_2 function. If
NULL
, as by default, this is set, depending on "psi" (for now only
"bisquare" and "optimal"), to a suitable value.
tuning constant vector for the rho_1 function in case
psi
is set to "rocke".
tuning constant vector for the rho_2 function in case
psi
is set to "rocke".
integer specifying the maximum number of IRWLS iterations.
(for the RWLS iterations algorithm of the fixed parameters): relative convergence tolerance for the parameter vector.
(for the optim
function used in the
estimation procedure of the random variance parameters): relative
convergence tolerance for the parameter vector.
relative convergence tolerance for the scale vector.
integer indicating if the progress of the algorithm should be traced (increasingly); default 'trace.lev = 0' does no tracing.
string specifying the estimator-chain. For now available procedures are 'compositeS', 'compositeTau' and 'S'. Default is set to 'compositeTau'.
string specifying the type psi-function used. Available choices for the composite methods are "bisquare" and "optimal". For classic methods "rocke", "bisquare" and "optimal". Defaut is set to "optimal".
logical. If TRUE
a robust simple regression is
performed for each explanatory variable in order to get starting
values for the fixed effect parameters.
logical. If TRUE
a simple regression is
performed for each explanatory variable in order to get starting
values for the random variance parameters.
string with function name to be used to calculate initial value of the fixed effect parameters. Possible values are "lmrob.S" and "lmRob".
function or string with function name to be used to calculate initial covariance matrix estimate if necessary. Possible string value is "TSGS", "2SGS" and "covOGK". Default is set to "TSGS".
logical. If TRUE
the estimated variance-covariance
matrix for the fixed and random parameters is reported.
further arguments.
Claudio Agostinelli and Victor J. Yohai
## Show the default settings:
str(varComprob.control())
Run the code above in your browser using DataLab