RaschModel

reweight.RaschModel

bread.RaschModel

estfun.RaschModel

character. Which type of derivatives should be used for computing
    gradient and Hessian matrix? Analytical with sum algorithm (<code>"sum"</code>),
    analytical with difference algorithm (<code>"diff"</code>, faster but numerically unstable),
    or 

deriv

logical. Should the Hessian of the final model be computed?
    If set to <code>FALSE</code>, the <code>vcov</code> method can only return <code>NA</code>s
    and consequently no standard errors or tests are available in the <code>summary</code>.

hessian

further arguments passed to <code><a href="/link/nlm?package=psychotree&version=0.12-2&to=stats" rd-options="stats" data-mini-rdoc="stats::nlm">nlm</a></code>.

gradtol, ...

<code>RaschModel</code> is a wrapper function that creates a <code>"StatModel"</code> object
  with certain fitting parameters passed on to <code><a href="/link/RaschModel.fit?package=psychotree&version=0.12-2&to=psychotools" rd-options="psychotools" data-mini-rdoc="psychotools::RaschModel.fit">RaschModel.fit</a></code> for fitting
  simple Rasch models.

tree

Recursive partitioning based on psychometric models,
        employing the general MOB algorithm (from package party) to
        obtain Bradley-Terry trees and Rasch trees.

RaschModel: Model-Generating Function for Rasch Models

Description

Usage

Arguments

Value

Details

See Also