VGAM (version 1.0-1)

vcovvlm: Calculate Variance-Covariance Matrix for a Fitted VLM or RR-VGLM Object

Description

Returns the variance-covariance matrix of the parameters of a fitted vlm-class object or a fitted rrvglm-class object.

Usage

vcov(object, ...)
vcovvlm(object, dispersion = NULL, untransform = FALSE)

Arguments

object

A fitted model object, having class vlm-class or rrvglm-class or a superclass of such. The former includes a

dispersion

Numerical. A value may be specified, else it is estimated for quasi-GLMs (e.g., method of moments). For almost all other types of VGLMs it is usually unity. The value is multiplied by the raw variance-covariance matrix.

untransform

logical. For intercept-only models with trivial constraints; if set TRUE then the parameter link function is inverted to give the answer for the untransformed/raw parameter.

...

Same as vcov.

Value

• Same as vcov.

Details

This methods function is based on the QR decomposition of the (large) VLM model matrix and working weight matrices. Currently vcovvlm operates on the fundamental vlm-class objects because pretty well all modelling functions in VGAM inherit from this. Currently vcovrrvglm is not entirely reliable because the elements of the A--C part of the matrix sometimes cannot be computed very accurately, so that the entire matrix is not positive-definite.

See Also

confintvglm, summaryvglm, vcov.

Examples

ndata <- data.frame(x2 = runif(nn <- 300))
ndata <- transform(ndata, y1 = rnbinom(nn, mu = exp(3+x2), size = exp(1)),
                          y2 = rnbinom(nn, mu = exp(2-x2), size = exp(0)))
fit1 <- vglm(cbind(y1, y2) ~ x2, negbinomial, data = ndata, trace = TRUE)
fit2 <- rrvglm(y1 ~ x2, negbinomial(zero = NULL), data = ndata)
coef(fit1, matrix = TRUE)
vcov(fit1)
vcov(fit2)