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 |