Generalised Linear Mixed Models in R

---

Documentation for package ‘glmmrBase’ version 0.8.1

• DESCRIPTION file.

Help Pages

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
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
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