corMatrix.corStruct {nlme} | R Documentation

## Matrix of a corStruct Object

### Description

This method function extracts the correlation matrix (or its transpose inverse square-root factor), or list of correlation matrices (or their transpose inverse square-root factors) corresponding to `covariate` and `object`. Letting S denote a correlation matrix, a square-root factor of S is any square matrix L such that S=L'L. When `corr = FALSE`, this method extracts L^(-t).

### Usage

    ## S3 method for class 'corStruct':
    corMatrix(object, covariate, corr, ...)

### Arguments

`object` | an object inheriting from class `corStruct` representing a correlation structure.
`covariate` | an optional covariate vector (matrix), or list of covariate vectors (matrices), at which values the correlation matrix, or list of correlation matrices, are to be evaluated. Defaults to `getCovariate(object)`.
`corr` | a logical value. If `TRUE` the function returns the correlation matrix, or list of correlation matrices, represented by `object`. If `FALSE` the function returns a transpose inverse square-root of the correlation matrix, or a list of transpose inverse square-root factors of the correlation matrices.
`...` | some methods for this generic require additional arguments. None are used in this method.

### Value

If `covariate` is a vector (matrix), the returned value will be an array with the corresponding correlation matrix (or its transpose inverse square-root factor). If the `covariate` is a list of vectors (matrices), the returned value will be a list with the correlation matrices (or their transpose inverse square-root factors) corresponding to each component of `covariate`.

### Author(s)

Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu

### References

Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer.

### See Also

`corFactor.corStruct`, `Initialize.corStruct`

### Examples

    cs1 <- corAR1(0.3)
    corMatrix(cs1, covariate = 1:4)
    corMatrix(cs1, covariate = 1:4, corr = FALSE)

    # Pinheiro and Bates, p. 225
    cs1CompSymm <- corCompSymm(value = 0.3, form = ~ 1 | Subject)
    cs1CompSymm <- Initialize(cs1CompSymm, data = Orthodont)
    corMatrix(cs1CompSymm)

    # Pinheiro and Bates, p. 226
    cs1Symm <- corSymm(value = c(0.2, 0.1, -0.1, 0, 0.2, 0),
                       form = ~ 1 | Subject)
    cs1Symm <- Initialize(cs1Symm, data = Orthodont)
    corMatrix(cs1Symm)

    # Pinheiro and Bates, p. 236
    cs1AR1 <- corAR1(0.8, form = ~ 1 | Subject)
    cs1AR1 <- Initialize(cs1AR1, data = Orthodont)
    corMatrix(cs1AR1)

    # Pinheiro and Bates, p. 237
    cs1ARMA <- corARMA(0.4, form = ~ 1 | Subject, q = 1)
    cs1ARMA <- Initialize(cs1ARMA, data = Orthodont)
    corMatrix(cs1ARMA)

    # Pinheiro and Bates, p. 238
    spatDat <- data.frame(x = (0:4)/4, y = (0:4)/4)
    cs1Exp <- corExp(1, form = ~ x + y)
    cs1Exp <- Initialize(cs1Exp, spatDat)
    corMatrix(cs1Exp)

[Package nlme version 3.1-89 Index]