simulate.blim: Simulate Responses from Basic Local Independence Models (BLIMs)

Description

Simulates responses from the distribution corresponding to a fitted blim model object.

Usage

# S3 method for blim
simulate(object, nsim = 1, seed = NULL, ...)

Value

A named vector of frequencies of response patterns.

Arguments

object: an object of class blim, typically the result of a call to blim.
nsim: currently not used.
seed: currently not used.
...: further arguments passed to or from other methods. None are used in this method.

Details

Responses are simulated in two steps: First, a knowledge state is drawn with probability P.K. Second, responses are generated by applying rbinom with probabilities computed from the model object's beta and eta components.

Examples

Run this code

data(DoignonFalmagne7)
 
m1 <- blim(DoignonFalmagne7$K, DoignonFalmagne7$N.R)
simulate(m1)

## Parametric bootstrap for the BLIM
disc <- replicate(200, blim(m1$K, simulate(m1))$discrepancy)

hist(disc, col = "lightgray", border = "white", freq = FALSE, breaks = 20,
     main = "BLIM parametric bootstrap", xlim = c(.05, .3))
abline(v = m1$discrepancy, lty = 2)

## Parameter recovery for the SLM
m0 <- list( P.K = getSlmPK( g = rep(.8, 5),
                            K = DoignonFalmagne7$K,
                           Ko = getKFringe(DoignonFalmagne7$K)),
           beta = rep(.1, 5),
            eta = rep(.1, 5),
              K = DoignonFalmagne7$K,
         ntotal = 800)
class(m0) <- c("slm", "blim")

pars <- replicate(20, coef(slm(m0$K, simulate(m0), method = "ML")))
boxplot(t(pars), horizontal = TRUE, las = 1,
        main = "SLM parameter recovery")

## See ?endm for further examples.