cold-class: Class `cold` of a maximum likelihood estimation

Description

This class encapsulates results of a maximum likelihood procedure.

Arguments

Objects from the Class

Objects can be created by calls of the form new("cold", ...), but most often as the result of a call to cold.

Slots

coefficients:: Object of class "matrix". Estimated parameters.
se:: Object of class "matrix". Standard errors of estimated parameters.
covariance:: Object of class "matrix". Covariance of estimated parameters.
correlation:: Object of class "matrix". Correlation of estimated parameters.
log.likelihood:: Object of class "numeric". The value of the log likelihood.
message:: Object of class "integer". A character string giving any additional information returned by the optimizer, or NULL. See optim for details.
n.cases:: Object of class "numeric". Number of individual profiles used in the optimization procedure.
ni.cases:: Object of class "numeric". Number of individual profiles in the dataset.
aic:: Object of class "numeric". The Akaike information criterion for a fitted model object.
Fitted:: Object of class "numeric". The fitted values for the estimated parameters.
bi.estimate:: Object of class "numeric". The estimated values for the individual random effects.
Fitted.av:: Object of class "numeric".
Time:: Object of class "numeric". Vector of time points.
model.matrix:: Object of class "matrix". The model matrix.
y.matrix:: Object of class "matrix". The matrix of response values.
random.matrix:: Object of class "matrix". The model matrix of random effects.
subset.data:: Object of class "data.frame". The data subset if considered.
final.data:: Object of class "data.frame". The data set considered.
y.av:: Object of class "numeric". The average of the response value over an individual profile.
data.id:: Object of class "numeric". Vector of individual observations.
call:: Object of class "language". The call to "cold".

Methods

anova: signature(object="cold"): Anova table.
coeftest: signature(object="cold"): A list of summary statistics of the fixed effects coefficients.
fitted: signature(object="cold"): The fitted values of a fitted model.
fixeff: signature(object="cold"): The values corresponding to the fixed effects of a fitted model.
getAIC: signature(object="cold"): A numeric value corresponding to the AIC of the fitted model.
getcoef: signature(object="cold"): The values corresponding to the coefficient estimates of the fitted model.
getLogLik: signature(object="cold"): A numeric value corresponding to the log-Likelihood of the fitted model.
getvcov: signature(object="cold"): The variance-covariance matrix of the fitted model.
model.mat: signature(object="cold"): The fixed effects model matrix of the fitted model.
plot: signature(x="cold", y="missing"): Plots three type of plots.
randeff: signature(object="cold"): A data frame corresponding to the conditional random effects of the fitted model.
show: signature(object="cold"): Display object briefly.
summary: signature(object="cold"): Generate object summary.
vareff: signature(object="cold"): Numeric value(s) corresponding to the estimated random effect(s) variance of the fitted model.