View source: R/mc_anova_dispersion.R
| mc_anova_dispersion | R Documentation |
Performs Wald tests to generate analysis-of-variance tables of the significance for the dispersion components by response variables for model objects produced by mcglm.
mc_anova_dispersion(object, p_var, names, verbose = TRUE)
object |
An object of |
p_var |
A list of indices that indicate how the dispersion parameters are related. Parameters with the same index are tested together. |
names |
Names to be shown in the table. |
verbose |
a logical if TRUE print some information about the tests performed. Default verbose = TRUE. |
Type III ANOVA table for dispersion components of mcglm objects.
Lineu Alberto Cavazani de Freitas, lineuacf@gmail.com
mc_anova_I, mc_anova_II and
mc_anova_III.
library(mcglm)
library(Matrix)
library(htmcglm)
data("soya", package = "mcglm")
form.grain <- grain ~ water * pot
form.seed <- seeds ~ water * pot
soya$viablepeasP <- soya$viablepeas / soya$totalpeas
form.peas <- viablepeasP ~ water * pot
Z0 <- mc_id(soya)
Z1 <- mc_mixed(~0 + factor(block), data = soya)
fit_joint <- mcglm(linear_pred = c(form.grain,
form.seed,
form.peas),
matrix_pred = list(c(Z0, Z1),
c(Z0, Z1),
c(Z0, Z1)),
link = c("identity",
"log",
"logit"),
variance = c("constant",
"tweedie",
"binomialP"),
Ntrial = list(NULL,
NULL,
soya$totalpeas),
power_fixed = c(TRUE,TRUE,TRUE),
data = soya)
mc_anova_dispersion(fit_joint,
p_var = list(c(0,1), c(0,1), c(0,1)),
names = list(c('tau10', 'tau11'),
c('tau20', 'tau21'),
c('tau30', 'tau31')))
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