logLikvlm: Extract Log-likelihood for VGLMs/VGAMs/etc.

In VGAM: Vector Generalized Linear and Additive Models

Extract Log-likelihood for VGLMs/VGAMs/etc.

Description

Calculates the log-likelihood value or the element-by-element contributions of the log-likelihood.

Usage

## S3 method for class 'vlm'
logLik(object, summation = TRUE, ...)

Arguments

object	Some VGAM object, for example, having class vglmff-class.
summation	Logical, apply sum? If FALSE then a n-vector or n-row matrix (with the number of responses as the number of columns) is returned. Each element is the contribution to the log-likelihood.
...	Currently unused. In the future: other possible arguments fed into logLik in order to compute the log-likelihood.

Details

By default, this function returns the log-likelihood of the object. Thus this code relies on the log-likelihood being defined, and computed, for the object.

Value

Returns the log-likelihood of the object. If summation = FALSE then a n-vector or n-row matrix (with the number of responses as the number of columns) is returned. Each element is the contribution to the log-likelihood. The prior weights are assimulated within the answer.

Warning

Not all VGAM family functions have had the summation checked.

Note

Not all VGAM family functions currently have the summation argument implemented.

Author(s)

T. W. Yee.

See Also

VGLMs are described in vglm-class; VGAMs are described in vgam-class; RR-VGLMs are described in rrvglm-class; AIC; anova.vglm.

Examples

zdata <- data.frame(x2 = runif(nn <- 50))
zdata <- transform(zdata, Ps01    = logitlink(-0.5       , inverse = TRUE),
                          Ps02    = logitlink( 0.5       , inverse = TRUE),
                          lambda1 =  loglink(-0.5 + 2*x2, inverse = TRUE),
                          lambda2 =  loglink( 0.5 + 2*x2, inverse = TRUE))
zdata <- transform(zdata, y1 = rzipois(nn, lambda = lambda1, pstr0 = Ps01),
                          y2 = rzipois(nn, lambda = lambda2, pstr0 = Ps02))

with(zdata, table(y1))  # Eyeball the data
with(zdata, table(y2))
fit2 <- vglm(cbind(y1, y2) ~ x2, zipoisson(zero = NULL), data = zdata)

logLik(fit2)  # Summed over the two responses
sum(logLik(fit2, sum = FALSE))  # For checking purposes
(ll.matrix <- logLik(fit2, sum = FALSE))  # nn x 2 matrix
colSums(ll.matrix)  # log-likelihood for each response

VGAM documentation built on Sept. 18, 2024, 9:09 a.m.