extractors: Functions to extract various components of a fit.

In spaMM: Mixed-Effect Models, with or without Spatial Random Effects

Functions to extract various components of a fit.

Description

Most extractors are methods of generic functions defined in base R (see Usage), for which the base documentation may be useful.

formula extracts the model formula.
family extracts the response family.
terms extracts the formula, with attributes describing the fixed-effect terms.
nobs returns the length of the response vector.
logLik extracts the log-likelihood (exact or approximated).
dev_resids returns a vector of squared (unscaled) deviance residuals (the summands defined for GLMs in McCullagh and Nelder 1989, p. 34; see Details of LL-family for other response families.
deviance returns the sum of squares of these deviance residuals, possibly weighted by prior weights (consistently with stats::deviance. See residuals.HLfit for details and comparison with related extractors.
fitted extracts fitted values.
response extracts the response (as a vector).
fixef extracts the fixed effects coefficients, \beta.
ranef extracts the predicted random effects, Lv (default since version 1.12.0), or optionally u (see random-effects for definitions). print.ranef controls their printing.
getDistMat returns a distance matrix for a geostatistical (Matérn etc.) random effect.
df.residual extracts residual degrees-of-freedom for fitted models (here number of observations minus number of parameters of the model except residual dispersion parameters). wweights extracts prior weights (as defined by the fitting functions's prior.weights argument).

Usage

## S3 method for class 'HLfit'
formula(x, which="hyper", ...)
## S3 method for class 'HLfit'
family(object, ...)
## S3 method for class 'HLfit'
terms(x, ...)
## S3 method for class 'HLfit'
nobs(object, ...)
## S3 method for class 'HLfit'
logLik(object, which, ...)
## S3 method for class 'HLfit'
fitted(object, ...)
## S3 method for class 'HLfit'
fixef(object, na.rm=NULL, ...)
## S3 method for class 'HLfit'
ranef(object, type = "correlated", ...)
## S3 method for class 'ranef'
print(x, max.print = 40L, ...)
## S3 method for class 'HLfit'
deviance(object, ...)
## S3 method for class 'HLfit'
df.residual(object, ...)
## S3 method for class 'HLfit'
weights(object, type, ...)
##
getDistMat(object, scaled=FALSE, which = 1L)
response(object,...)
dev_resids(object,...)

Arguments

object	An object of class HLfit, as returned by the fitting functions in spaMM.
type	For ranef, use type="correlated" (default) to display the correlated random effects (Lv), whether in a spatial model, or a random- coefficient model. Use type="uncorrelated" to pretty-print the elements of the <object>$ranef vector (u). For weights, either "prior" or "working", with the same meaning as for weights.glm: respectively the prior weights, or the weights used in the final iteration of the IRLS algorithm.
which	* For logLik, the name of the element of the APHLs list to return (see Details for any further possibility). The default depends on the fitting method. In particular, if it was REML or one of its variants, the default is to return the log restricted likelihood (exact or approximated). * For getDistMat, an integer, to select a random effect from several for which a distance matrix may be constructed. * For formula, by default the model formula with non-expanded multIMRF random-effect terms is returned, while for which="" a formula with multIMRF terms expanded as IMRF terms is returned.
na.rm	Whether to include NA values for missing coefficients of rank-deficient model matrices. Default is to exclude them for mixed models and to include them for other ones. See Details for the underlying reason.
scaled	If FALSE, the function ignores the scale parameter \rho and returns unscaled distance.
x	For print.ranef: the return value of ranef.HLfit.
max.print	Controls options("max.print") locally.
...	Other arguments that may be needed by some method.

Details

For rank-deficient model matrices, base R procedures lm and glm estimate coefficients for a rank-trimmed matrix and coefficient() returns a full-length vector completed with NA values for coefficients not estimated, while the lme4 fixef method returns a trimmed vector. spaMM has long followed the base R convention for all models but this may impede use of some post-fit procedures initially conceived for lme4 objects (such as lmerTest procedures for LMMs). So now fixef.HLfit trims the vector by default for mixed-effect models only. The default is thus to maximize consistency/compatibility with preexisting procedures despite their inconsistencies with each other.

Value

formula returns a formula, except a list of them from fitmv() output.

terms returns an object of class c("terms", "formula") which contains the terms representation of a symbolic model. See terms.object for its structure. terms(<fitmv() result>) returns a list of such terms.

Other return values are numeric (for logLik), vectors (most cases), matrices or dist objects (for getDistMat), or a family object (for family). ranef returns a list of vectors or matrices (the latter for random-coefficient terms).

References

McCullagh, P. and Nelder J. A. (1989) Generalized linear models. Second ed. Chapman & Hall: London.

See Also

See summary.HLfit whose return value include the tables of fixed-effects coefficients and random-effect variances displayed by the summary, residuals.HLfit to extract various residuals, residVar to extract residual variances or information about residual variance models, hatvalues to extract leverages, get_matrix to extract the model matrix and derived matrices, and vcov.HLfit to extract covariances matrices from a fit, get_RLRsim_args to extract arguments for (notably) tests of random effects in LMMs.

Examples

data("wafers")
m1 <- fitme(y ~ X1+X2+(1|batch), data=wafers)
fixef(m1)
ranef(m1)

data("blackcap")
fitobject <- fitme(migStatus ~ 1 + Matern(1|longitude+latitude),data=blackcap,
                       fixed=list(nu=4,rho=0.4,phi=0.05))
getDistMat(fitobject)

spaMM documentation built on June 22, 2024, 9:48 a.m.