log_likelihood_shash

This function computes the negative log-likelihood for a Sinh-Arcsinh regression model
where the location, scale, and skewness parameters are modeled as functions of predictors.

internal

A comprehensive toolkit for generating continuous test norms in
psychometrics and biometrics, and analyzing model fit. The package offers both
distribution-free modeling using Taylor polynomials and parametric modeling
using the beta-binomial and the 'Sinh-Arcsinh' distribution. Originally developed
for achievement tests, it is applicable to a wide range of mental, physical, or
other test scores dependent on continuous or discrete explanatory variables. The
package provides several advantages: It minimizes deviations from representativeness
in subsamples, interpolates between discrete levels of explanatory variables,
and significantly reduces the required sample size compared to conventional
norming per age group. cNORM enables graphical and analytical evaluation of
model fit, accommodates a wide range of scales including those with negative
and descending values, and even supports conventional norming. It generates
norm tables including confidence intervals. It also includes methods for
addressing representativeness issues through Iterative Proportional Fitting.

Wolfgang Lenhard

cNORM

Continuous Norming

Alexandra Lenhard

Sebastian Gary

WPS publisher 

log_likelihood_shash function

<dl><dt>params</dt>
<dd>A numeric vector containing all model parameters</dd>
<dt>X_mu</dt>
<dd>Design matrix for location parameter</dd>
<dt>X_sigma</dt>
<dd>Design matrix for scale parameter</dd>
<dt>X_epsilon</dt>
<dd>Design matrix for skewness parameter</dd>
<dt>X_delta</dt>
<dd>Design matrix for tails</dd>
<dt>y</dt>
<dd>Response vector</dd>
<dt>weights</dt>
<dd>Observation weights</dd>
<dt>fixed_delta</dt>
<dd>If not NULL, the delta parameter is fixed to this value</dd></dl>

Arguments

Calculate the negative log-likelihood for a ShaSh regression model — log_likelihood_shash

<dl>

<dt>params</dt>
<dd>A numeric vector containing all model parameters</dd>


<dt>X_mu</dt>
<dd>Design matrix for location parameter</dd>


<dt>X_sigma</dt>
<dd>Design matrix for scale parameter</dd>


<dt>X_epsilon</dt>
<dd>Design matrix for skewness parameter</dd>


<dt>X_delta</dt>
<dd>Design matrix for tails</dd>


<dt>y</dt>
<dd>Response vector</dd>


<dt>weights</dt>
<dd>Observation weights</dd>


<dt>fixed_delta</dt>
<dd>If not NULL, the delta parameter is fixed to this value</dd>

</dl>

log_likelihood_shash: Calculate the negative log-likelihood for a ShaSh regression model

Description

Usage

Value

Arguments