# R/eps_CC_test_simple_E.R In theabjorn/extremesampling: Asymptotic tests and model fitting for extreme phenotype sampling

```eps_CC_test_simple_E = function(y,xg,l,u){

n = length(y)
ng = dim(xg)[2]
Xe = cbind(rep(1,n))

# Make one test statistics for ng genetic variants simultaneuosly

fit = epsCC.loglikmax(cbind(y),l,u)
beta = fit[1:(length(fit)-1)]
sigma = fit[length(fit)]
sigma2 = sigma*sigma

xbeta = Xe%*%beta
f = y-xbeta
zl = (l-xbeta)/sigma
zu = (u-xbeta)/sigma

h0 = (-dnorm(zu)+dnorm(zl))/(1-pnorm(zu)+pnorm(zl))
h1 = (-dnorm(zu)*zu+dnorm(zl)*zl)/(1-pnorm(zu)+pnorm(zl))
h2 = (-dnorm(zu)*zu*zu+dnorm(zl)*zl*zl)/(1-pnorm(zu)+pnorm(zl))
h3 = (-dnorm(zu)*zu*zu*zu+dnorm(zl)*zl*zl*zl)/(1-pnorm(zu)+pnorm(zl))

a = c(1 - h1 - h0*h0)
b = c(- h0 - h2 - h0*h1)
c = 2 - c(h1 + h3 + h1*h1)

I11_11 = crossprod(Xe,Xe*a) # t(Xe)%*%(diag(a)%*%Xe)

I11_22 = sum(c)

I11_12 = crossprod(Xe,b) # t(Xe)%*%(b)
I11_21 = t(I11_12)

I11 = rbind(cbind(I11_11, I11_12),
cbind(I11_21, I11_22))

I22 = crossprod(xg,xg*a)

I12 = crossprod(xg,cbind(Xe*a,b))

Sigma = (I22 - I12%*%tcrossprod(solve(I11),I12))/sigma2

s = crossprod(xg,y-xbeta + sigma*h0)/sigma2

t = crossprod(s,crossprod(ginv(Sigma),s))

pvalue = pchisq(t,ng,lower.tail=FALSE)
statistic = t
result = list(statistic,pvalue)
names(result) = c("statistic","p.value")
return(result)
}
```
theabjorn/extremesampling documentation built on May 31, 2019, 9:10 a.m.