residuals.nlmeStruct: Calculate nlmeStruct Residuals

In nlme: Linear and Nonlinear Mixed Effects Models

Calculate nlmeStruct Residuals

Description

The residuals at level i are obtained by subtracting the fitted values at that level from the response vector. The fitted values at level i are obtained by adding together the contributions from the estimated fixed effects and the estimated random effects at levels less or equal to i and evaluating the model function at the resulting estimated parameters.

Usage

## S3 method for class 'nlmeStruct'
residuals(object, level, conLin, ...)

Arguments

object	an object inheriting from class "nlmeStruct", representing a list of mixed-effects model components, such as reStruct, corStruct, and varFunc objects.
level	an optional integer vector giving the level(s) of grouping to be used in extracting the residuals from object. Level values increase from outermost to innermost grouping, with level zero corresponding to the population fitted values. Defaults to the highest or innermost level of grouping.
conLin	an optional condensed linear model object, consisting of a list with components "Xy", corresponding to a regression matrix (X) combined with a response vector (y), and "logLik", corresponding to the log-likelihood of the underlying nlme model. Defaults to attr(object, "conLin").
...	optional arguments to the residuals generic. Not used.

Value

if a single level of grouping is specified in level, the returned value is a vector with the residuals at the desired level; else, when multiple grouping levels are specified in level, the returned object is a matrix with columns given by the residuals at different levels.

Note

This method function is primarily used within the nlme function.

Author(s)

José Pinheiro and Douglas Bates [e-mail]

References

Bates, D.M. and Pinheiro, J.C. (1998) "Computational methods for multilevel models" available in PostScript or PDF formats at http://nlme.stat.wisc.edu

See Also

nlme, fitted.nlmeStruct

nlme documentation built on Nov. 27, 2023, 5:09 p.m.