nlme (version 3.1-99)

reStruct: Random Effects Structure

Description

This function is a constructor for the reStruct class, representing a random effects structure and consisting of a list of pdMat objects, plus a settings attribute containing information for the optimization algorithm used to fit the associated mixed-effects model.

Usage

reStruct(object, pdClass, REML, data)
## S3 method for class 'reStruct':
print(x, sigma, reEstimates, verbose, \dots)

Arguments

object

any of the following: (i) a one-sided formula of the form ~x1+...+xn | g1/.../gm, with x1+...+xn specifying the model for the random effects and g1/.../gm the grouping structure (m may be equal

pdClass

an optional character string with the name of the pdMat class to be used for the formulas in object. Defaults to "pdSymm" which corresponds to a general positive-definite matrix.

REML

an optional logical value. If TRUE, the associated mixed-effects model will be fitted using restricted maximum likelihood; else, if FALSE, maximum likelihood will be used. Defaults to FALSE.

data

an optional data frame in which to evaluate the variables used in the random effects formulas in object. It is used to obtain the levels for factors, which affect the dimensions and the row/column names of the underlying

x

an object inheriting from class reStruct to be printed.

sigma

an optional numeric value used as a multiplier for the square-root factors of the pdMat components (usually the estimated within-group standard deviation from a mixed-effects model). Defaults to 1.

reEstimates

an optional list with the random effects estimates for each level of grouping. Only used when verbose = TRUE.

verbose

an optional logical value determining if the random effects estimates should be printed. Defaults to FALSE.

...

Optional arguments can be given to other methods for this generic. None are used in this method.

Value

• an object inheriting from class reStruct, representing a random effects structure.

See Also

groupedData, lme, pdMat, solve.reStruct, summary.reStruct, update.reStruct

Examples

rs1 <- reStruct(list(Dog = ~day, Side = ~1), data = Pixel)
rs1