null_perm_m0 {trc}R Documentation

Procedure for estimating the null distribution of the TRC tau with a given m value

Description

Procedure for estimating the null distribution of the TRC tau with a given m value.

Usage

null_perm_m0(X,Y,nperm=1000,m=5,seed=21)

Arguments

X

An observed data vector from the first condition.

Y

An observed data vector from the second condition.

nperm

the number of permutations to estimate the null distribution (default: 1000).

m

A rank threshold for the calculation of TRC tau (default: 5).

seed

An initial seed for the permutation.

Details

Null distribution of the TRC tau with a given m value is estimated by the permuted samples.

Value

perm_tau

A vector of calculated TRC tau values from the permuted samples

References

Lim, J., Yu, D., Kuo, H., Choi, H., and Walmsely, S. (2019). Truncated Rank Correlation as a robust measure of test-retest reliability in mass spectrometry data. Statistical Applications in Genetics and Molecular Biology, 18(4).

Examples

p = 100
sig_z = 1.15
sig_e = 1
mu_z = 2
mu_e = 8
m0 = 30

S1 = rnorm(p,mean=mu_e,sd=sig_e)
S2 = rnorm(p,mean=mu_e,sd=sig_e)
    
if(m0!=0)
{
   X = mu_z + rnorm(m0,mean=0,sd=sig_z)
   indx = 1:p
   s_indx = sort(sample(indx,m0))
   S1[s_indx] = S1[s_indx] + X
   S2[s_indx] = S2[s_indx] + X
}
      
S1 = exp(S1)
S2 = exp(S2)

null_res = null_perm_m0(S1,S2,nperm=1000,m=5,seed=21)


[Package trc version 0.2 Index]