Description
asr_families specifies the details of the models accepted by the family argument to asreml.
Usage
asr_gaussian(link = "identity", dispersion = NA)
asr_Gamma(link = "inverse", dispersion = 1, phi = 1)
asr_inverse.gaussian(link = "1/mu^2", dispersion = NA)
asr_binomial(link = "logit", dispersion = 1, total = NULL)
asr_multinomial(link = "logit", dispersion = 1, total = NULL)
asr_negative.binomial(link = "log", dispersion = 1, phi = 1)
asr_poisson(link = "log", dispersion = 1)
Arguments
link |
A character string identifying the link function; valid values are: Gaussian: identity, log, inverse Gamma: identity, log, inverse inverse.gaussian: 1/mu^2, identity, log, inverse binomial: logit, probit, cloglog multinomial: logit, probit, cloglog negative.binomial: identity, log, inverse poisson: identity, log, sqrt |
dispersion |
If NA, the default for Gaussian and inverse Gaussian models, the dispersion parameter is estimated, otherwise it is fixed at the nominated value (default 1.0). |
phi |
The known value of the additional parameter phi. |
total |
A character string or name giving the column in data containing the totalcounts. |
Value
A list of functions and expressions needed by the family argument.
Functions
asr_gaussian: |
The Gaussian model (default). |
asr_Gamma |
The gamma model. |
asr_inverse.gaussian |
The inverse Gaussian model. |
asr_binomial |
The binomial model. If the response is between 0 and 1 it is interpreted as the proportion of successes, otherwise, if not a binary (0,1) variate, it is interpreted as counts of successes; the total number of cases is given by the total argument. If total is NULL, a binary (0,1) response is expected. |
asr_multinomial |
The multinomial model. The response can either be a matrix of counts with the response categories as columns, with an additional column for the total number of cases in each row, or in univariate style with the response as a factor. If the response is a matrix and total=NULL, the total counts are calculated from the category columns. |
asr_negative.binomial |
The negative-binomial model. |
asr_poisson |
The poisson model. |