Simulate Responses from Basic Local Independence Models (BLIMs)

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

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

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.

Value

A named vector of frequencies of response patterns.

See also

blim, endm.

Examples

data(DoignonFalmagne7)
 
m1 <- blim(DoignonFalmagne7$K, DoignonFalmagne7$N.R)
simulate(m1)
#> 00000 00001 00010 00100 00101 00110 01000 01001 01010 01100 01101 01110 01111 
#>    84     6     3     8     1     1    97     7    16    15    12    13    15 
#> 10000 10001 10010 10100 10101 10110 10111 11000 11001 11010 11011 11100 11101 
#>   111     8    19     8    12    11    16    63     8    79     9    69    92 
#> 11110 11111 
#>   103   114 

## 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.