chi.norm

A transformation of Chi-squared random variable to make it normal like.

Implements several methods for testing the variance component parameter in regression models that contain kernel-based random effects, including a maximum of adjusted scores test. Several kernels are supported, including a profile hidden Markov model mutual information kernel for protein sequence. This package is described in Fong et al. (2015) <DOI:10.1093/biostatistics/kxu056>.

Youyi Fong

Kernel Based Regression Models

Saheli Datta

Krisztian Sebestyen

Steve Park

Dave Geyer

chi.norm function

<dl> <dt>q</dt>
<dd>numeric. A random variable following chi-squared distribution</dd> <dt>v</dt>
<dd>numeric. A random variable following normal distribution</dd></dl>

Arguments

A Transformation of Chi-squared Random Variable — chi.norm

<dl>

 <dt>q</dt>
<dd>numeric. A random variable following chi-squared distribution</dd>

 <dt>v</dt>
<dd>numeric. A random variable following normal distribution</dd>

</dl>

chi.norm: A Transformation of Chi-squared Random Variable

Description

Usage

Arguments