# Lmat: Generate a hypothesis matrix In gmonette/spida: Collection of miscellaneous functions for mixed models etc. prepared for SPIDA 2009+ (development version)

## Description

Generates a hypothesis matrix to test whether a group of coefficients in a linear model are jointly zero, selecting the coefficients that match a regular expression.

## Usage

 `1` ```Lmat(fit, pattern) ```

## Arguments

 `fit` `pattern`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50``` ```##---- Should be DIRECTLY executable !! ---- ##-- ==> Define data, use random, ##-- or do help(data=index) for the standard data sets. ## The function is currently defined as function (fit, pattern) { umatch <- function(pat, x) { ret <- rep(0, length(pat)) for (ii in 1:length(pat)) { imatch <- grep(pat[ii], x) if (length(imatch) != 1) { cat("\nBad match of:\n") print(pat) cat("in:\n") print(x) stop("Bad match") } ret[ii] <- imatch } ret } if (is.character(fit)) { x <- pattern pattern <- fit fit <- x } fe <- getFix(fit)\$fixed ne <- names(fe) if (is.character(pattern)) { L.indices <- grep(pattern, names(fe)) ret <- diag(length(fe))[L.indices, , drop = F] rownames(ret) <- names(fe)[L.indices] labs(ret) <- "Coefficients" } else if (is.list(pattern)) { ret <- matrix(0, nrow = length(pattern), ncol = length(fe)) colnames(ret) <- ne for (ii in 1:length(pattern)) { Lcoefs <- pattern[[ii]] pos <- umatch(names(Lcoefs), ne) if (any(is.na(pos))) stop("Names of L coefs not matched in fixed effects") ret[ii, pos] <- Lcoefs } rownames(ret) <- names(pattern) } labs(ret) <- "Coefficients" ret } ```

gmonette/spida documentation built on May 14, 2017, 1 p.m.