# omniRLRT_fast: Composite kernel machine regression based restricted... In CKLRT: Composite Kernel Machine Regression Based on Likelihood Ratio Test

## Description

Composite kernel machine regression based restricted likelihood ratio test

## Usage

 ```1 2``` ```omniRLRT_fast(y, X, K1, K2, N = 10000, length.rho = 200, length.lambda = 21) ```

## Arguments

 `y` vector of the continous outcomes. `X` the additional covariates. `K1` the first kernel corresponding to the genetic main effect. `K2` the second kernel corresponding to the genetic and environment interaction effect. `N` total number of randomly generated normal variables used to generate the emprical null distribution of LRT. Default value is 10,000. `length.rho` the length of rho. Default value is 21. The values of rho are between 0 and 1. `length.lambda` the length of lambda. Dafult value is 200. The values of lambda are all more than 0.

## Value

the result is a list containing three elements. 1. p.dir is the p-value of restricted likelihood ratio test based on emprical distrition. 2. p.aud is the p-value by approximating the null distribution as a mixture of a point mass at zero with probability b and weighted chi square distribution with d degrees of freedom with probality of 1-b. 3. LR is the likelihood ratio test statistics.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```set.seed(6) n = 50 # the number of observations X = rnorm(n) # the other covariates p = 2 # two snp in a gene will be simulated G = runif(n*p)< 0.5 G = G + runif(n*p) < 0.5 G = matrix(G, n,p) #genetic matrix E = (runif(n) < 0.5)^2 #enviroment effect y = rnorm(n) + G[,1] * 0.3 #observations omniRLRT_fast(y, X = cbind(X, E),K1 = G %*% t(G),K2 = (G*E) %*% t(G * E)) ```

CKLRT documentation built on May 1, 2019, 10:20 p.m.