Operations on lists of parameters
get_ranPars returns various subsets of random-effect parameters (correlation or variance parameters), as controlled by its which argument.
It is one of several extractors for fixed or estimated parameters of different classes of parameters, for which a quick guide is
get_ranPars: for random-effect parameters, excluding residual dispersion;VarCorr: alternative extractor for random-effect (co)variance and optionally residual variance, in a data frame format;residVar: for residual variance parameters, family dispersion parameters, or information about residual variance models;get_residVar: alternative extractor of residual variances with different features inherited from get_predVar;get_inits_from_fit: extracts estimated parameters from a fit.
remove_from_parlist removes elements from a list of parameters, and from its type attribute.
get_ranPars(object, which=NULL, ...) remove_from_parlist(parlist, removand=NULL, rm_names=names(unlist(removand)))
object |
An object of class |
which |
NULL or character string. Use |
... |
Other arguments that may be needed by some method. |
parlist |
A list of parameters. see Details. |
removand |
Optional. A list of parameters to be removed from |
rm_names |
Names of parameters to be removed from |
For heteroscedastic models, such as conditional autoregressive models, the variance parameter “lambda” refers to a common scaling coefficient. For other random-effect models, “lambda” typically refers to the single variance parameter.
remove_from_parlist is designed to manipulate structured lists of parameters, such as a list with elements phi, lambda, and corrPars, the latter being itself a list structured as the return value of get_ranPars(.,which="corrPars"). parlist may have an attribute type, also with elements phi, lambda, and corrPars... If given, removand must have the same structure (but typically not all the elements of parlist); otherwise, rm_names must have elements which match names of unlist(names(parlist)).
get_ranPars(.,which="corrPars") returns a (possibly nested) list of correlation parameters (or NULL if there is no such parameter). Top-level elements correspond to the different random effects. The list has a "type" attribute having the same nested-list structure and describing whether and how the parameters where fitted: "fix" means they where fixed, not fitted; "var" means they were fitted by HLfit's specific algorithms; "outer" means they were fitted by a generic optimization method.
get_ranPars(.,which="lambda") returns a vector of variance values, one per random effect, including both “outer”- and “inner”-optimized ones.
get_ranPars(.,which="outer_lambda") returns only “outer”-optimized variance parameters, ignoring those fitted by HLfit's specific algorithms.
get_ranPars(. which="ranef_var") (experimental) returns a list with elements
Varsame as get_ranPars(.,which="lambda")
lembda_estA vector of variance values, one for each level of each random effect
outerA vector or outer-optimized variance values, as returned by get_ranPars(.,which="outer_lambda")
Other elements, subject to change in later versions.
remove_from_parlist returns a list of model parameters with given elements removed, and likewise for its (optional) type attribute. See Details for context of application.
See VarCorr, residVar, get_residVar, or get_inits_from_fit as described in in the quick guide above.
data("wafers")
m1 <- HLfit(y ~X1+X2+(1|batch), resid.model = ~ 1, data=wafers, method="ML")
get_ranPars(m1,which="corrPars") # NULL since no correlated random effect
parlist1 <- list(lambda=1,phi=2,corrPars=list("1"=list(rho=3,nu=4),"2"=list(rho=5)))
parlist2 <- list(lambda=NA,corrPars=list("1"=list(rho=NA))) # values of elements do not matter
remove_from_parlist(parlist1,parlist2) ## same result as:
remove_from_parlist(parlist1,rm_names = names(unlist(parlist2)))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.