pickCoef {gnm}

Get Indices or Values of Selected Model Coefficients

Description

Get the indices or values of a subset of non-eliminated coefficients selected via a Tk dialog or by pattern matching.

Usage

pickCoef(object, pattern = NULL, value = FALSE, ...)

Arguments

object

a model object.

pattern

character string containing a regular expression or (with fixed = TRUE) a pattern to be matched exactly. If NULL, a Tk dialog will open for coefficient selection.

value

if FALSE, a named vector of indices, otherwise the value of the selected coefficients.

...

arguments to pass on to pickFrom if pattern is missing, otherwise grep. In particular, fixed = TRUE specifies that pattern is a string to be matched as is.

Value

If value = FALSE (the default), a named vector of indices, otherwise the values of the selected coefficients. If no coefficients are selected the returned value will be NULL.

Author(s)

Heather Turner

See Also

regexp, grep, pickFrom, ofInterest

Examples

set.seed(1)

### Extract indices for use with ofInterest

## fit the "UNIDIFF" mobility model across education levels
unidiff <- gnm(Freq ~ educ*orig + educ*dest +
               Mult(Exp(educ), orig:dest),
               family = poisson, data = yaish, subset = (dest != 7))

## set coefficients in first constituent multiplier as 'ofInterest'
## using regular expression
ofInterest(unidiff) <- pickCoef(unidiff, "[.]educ")

## summarise model, only showing coefficients of interest
summary(unidiff)

## get contrasts of these coefficients
getContrasts(unidiff, ofInterest(unidiff))

### Extract coefficients to use as starting values

## fit diagonal reference model with constant weights
set.seed(1)

## reconstruct counts voting Labour/non-Labour
count <- with(voting, percentage/100 * total)
yvar <- cbind(count, voting$total - count)

classMobility <- gnm(yvar ~ -1 + Dref(origin, destination), 
                     family = binomial, data = voting)

## create factors indicating movement in and out of salariat (class 1)
upward <- with(voting, origin != 1 & destination == 1)
downward <- with(voting, origin == 1 & destination != 1)

## extract diagonal effects from first model to use as starting values
diagCoef <- pickCoef(classMobility, "Dref(., .)", fixed = TRUE,
                     value = TRUE)

## fit separate weights for the "socially mobile" groups
## -- there are now 3 parameters for each weight
socialMobility <- gnm(yvar ~ -1 + Dref(origin, destination,
                                       delta = ~ 1 + downward + upward),
                      family = binomial, data = voting,
                      start = c(rep(NA, 6), diagCoef))