Generalised Linear Mixed Models in R


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Documentation for package ‘glmmrBase’ version 0.9.2

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glmmrBase-package Generalised Linear Mixed Models in R
Beta Beta distribution declaration
coef.mcml Extracts fixed effect coefficients from a mcml object
coef.Model Extracts coefficients from a Model object
confint.mcml Fixed effect confidence intervals for a 'mcml' object
Covariance R6 Class representing a covariance function and data
cross_df Generate crossed block structure
cycles Generates all the orderings of a
family.mcml Extracts the family from a 'mcml' object.
family.Model Extracts the family from a 'Model' object. This information can also be accessed directly from the Model as 'Model$family'
fitted.mcml Fitted values from a 'mcml' object
fitted.Model Extract or generate fitted values from a 'Model' object
fixed.effects Extracts the fixed effect estimates
formula.mcml Extracts the formula from a 'mcml' object.
formula.Model Extracts the formula from a 'Model' object
glmmrBase Generalised Linear Mixed Models in R
lme4_to_glmmr Map lme4 formula to glmmrBase formula
logLik.mcml Extracts the log-likelihood from an mcml object
logLik.Model Extracts the log-likelihood from an mcml object
match_rows Generate matrix mapping between data frames
mcml_glmer lme4 style generlized linear mixed model
mcml_lmer lme4 style linear mixed model
mcnr_family Returns the file name and type for MCNR function
MeanFunction R6 Class representing a mean function/linear predictor
Model A GLMM Model
nelder Generates a block experimental structure using Nelder's formula
nest_df Generate nested block structure
predict.mcml Predict from a 'mcml' object
predict.Model Generate predictions at new values from a 'Model' object
print.mcml Prints an mcml fit output
progress_bar Generates a progress bar
random.effects Extracts the random effect estimates
residuals.mcml Residuals method for a 'mcml' object
residuals.Model Extract residuals from a 'Model' object
setParallel Disable or enable parallelised computing
summary.mcml Summarises an mcml fit output
summary.Model Summarizes a 'Model' object
vcov.mcml Extract the Variance-Covariance matrix for a 'mcml' object
vcov.Model Calculate Variance-Covariance matrix for a 'Model' object
yexample312a Data for first example in Section 3.12 of JSS paper
yexample312b Data for second example in Section 3.12 of JSS paper
yexample312c Data for third example in Section 3.12 of JSS paper
ytest1 Data for model tests