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 in McCullagh and Nelder 1989, p. 34).
deviance returns the sum of squares of these (unscaled) deviance residuals, that is (consistently with stats::deviance) the unscaled deviance.
fitted extracts fitted values (see 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 u (see Details in HLfit for definitions), print.ranef controls their printing.
getDistMat returns a distance matrix for a geostatistical (Mat<U+00E9>rn etc.) random effect.
# S3 method for HLfit
formula(x, which="hyper", ...)
# S3 method for HLfit
family(object, ...)
# S3 method for HLfit
terms(x, ...)
# S3 method for HLfit
nobs(object, ...)
# S3 method for HLfit
logLik(object, which, ...)
# S3 method for HLfit
fitted(object, ...)
# S3 method for HLfit
fixef(object, ...)
# S3 method for HLfit
ranef(object, type = "correlated", ...)
# S3 method for ranef
print(x, max.print = 40L, ...)
# S3 method for HLfit
deviance(object, ...)
##
getDistMat(object, scaled=FALSE, which = 1L)
response(object,...)
dev_resids(object,...)An object of class HLfit, as returned by the fitting functions in spaMM.
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 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 function returns 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.
If FALSE, the function ignores the scale parameter \(rho\) and returns unscaled distance.
For print.ranef: the return value of ranef.HLfit.
Controls options("max.print") locally.
Other arguments that may be needed by some method.
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).
With which="LogL_Lap", logLik() returns a Laplace approximation of log-likelihood based on the observed Hessian, rather than the expected Hessian. This is implemented only for the case family=Gamma(log), for demonstration purposes.
McCullagh, P. and Nelder J. A. (1989) Generalized linear models. Second ed. Chapman & Hall: London.
Lee, Y., Nelder, J. A. (2001) Hierarchical generalised linear models: A synthesis of generalised linear models, random-effect models and structured dispersions. Biometrika 88, 987-1006.
Lee, Y., Nelder, J. A. and Pawitan, Y. (2006) Generalized linear models with random effects: unified analysis via h-likelihood. Chapman & Hall: London.
See 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.
# NOT RUN {
data("wafers")
m1 <- HLfit(y ~ X1+X2+(1|batch), resid.model = ~ 1,
data=wafers, method="ML")
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)
# }
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