| createGroup {mirt} | R Documentation |
Initializes the proper S4 class and methods necessary for mirt functions to use in estimation for definiting
customized group-level functions. To use the defined objects pass to the
mirt(..., customGroup = OBJECT) command, and ensure that the class parameters are properly labeled.
createGroup(par, est, den, nfact, gr = NULL, hss = NULL, gen = NULL, lbound = NULL, ubound = NULL, derivType = "Richardson")
par |
a named vector of the starting values for the parameters |
est |
a logical vector indicating which parameters should be freely estimated by default |
den |
the probability density function given the Theta/ability values.
First input contains a vector of all the defined parameters and the second input
must be a matrix called |
nfact |
number of factors required for the model. E.g., for unidimensional models with only one
dimension of integration |
gr |
gradient function (vector of first derivatives) of the log-likelihood used in
estimation. The function must be of the form |
hss |
Hessian function (matrix of second derivatives) of the log-likelihood used in
estimation. If not specified a numeric approximation will be used.
The input is idential to the |
gen |
a function used when |
lbound |
optional vector indicating the lower bounds of the parameters. If not specified then the bounds will be set to -Inf |
ubound |
optional vector indicating the lower bounds of the parameters. If not specified then the bounds will be set to Inf |
derivType |
if the |
Phil Chalmers rphilip.chalmers@gmail.com
## Not run: # normal density example den <- function(obj, Theta) dnorm(Theta, obj@par[1], obj@par[2]) par <- c(mu = 0, sigma = 1) est <- c(FALSE, TRUE) lbound <- c(-Inf, 0) grp <- createGroup(par, est, den, nfact = 1, lbound=lbound) mod <- mirt(Science, 1, 'Rasch') modcustom <- mirt(Science, 1, 'Rasch', customGroup=grp) coef(mod) coef(modcustom) ## End(Not run)