| logLik.vlm {VGAM} | R Documentation |
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 |
summation |
Logical, apply |
... |
Currently unused.
In the future:
other possible arguments fed into
|
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