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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