gwrpv_batch {gwrpvr} | R Documentation |
Batch computation of a list of pvalues of GWA regression beta statistics using a bernoulli-normal mixture distribution
Description
Batch computation of a list of pvalues of GWA regression beta statistics using a bernoulli-normal mixture distribution
Usage
gwrpv_batch(regresults, mua, siga, mub, sigb, pa, pb, logdelta = -16,
lognearnorm = -5, logtopsum = 8)
Arguments
regresults |
a list of four lists.
|
mua |
parameter of the mixture distribution, can be any real number |
siga |
parameter of the mixture distribution, can be any real number |
mub |
parameter of the mixture distribution, can be any real number |
sigb |
parameter of the mixture distribution, can be any real number |
pa |
parameter of the mixture distribution, a real number between zero and one with pa+pb=1 |
pb |
parameter of the mixture distribution, a real number between zero and one with pa+pb=1 |
logdelta |
must be in log base 10 format, with default value set to -16 |
lognearnorm |
must be in log base 10 format, with default value set to -5 |
logtopsum |
must be in log base 10 format, with default value set to 8 |
Value
gwrpv_batch returns a list of lists containing the lists:
- $pvalue
p-value of a two-sided hypothesis test for a true coefficient of zero
- $skew
skewness
- $kurt
kurtosis of the coefficient estimate under assumed model
- $skiptype
type of trimming/skip which took place (zero means no trimming)
- $totnobs
total number of observations
- $loopruns
number of sums in the main computation for each regression case
.
Examples
beta <- c(6.05879, -6.05879, 2.72055, -2.72055, 1.93347,
-1.93347, 0.88288, -0.88288, 4.28421, -4.28421)
n0 <- c(499, 499, 495, 495, 490, 490, 451, 451, 998, 998)
n1 <- c(1, 1, 5, 5, 10, 10, 48, 48, 2, 2)
n2 <- c(0, 0, 0, 0, 0, 0, 1, 1, 0, 0)
myregresults <- list(beta = beta, n0 = n0, n1 = n1, n2 = n2)
mua <- 13.87226
siga <- 2.58807
mub <- 4.62829
sigb <- 2.51803
pa <- 0.96544
pb <- 1.0 - pa
gwrpv_batch(myregresults,mua,siga,mub,sigb,pa,pb)
# store results in a user-defined variable g
g <- gwrpv_batch(myregresults,mua,siga,mub,sigb,pa,pb,logdelta=-16,lognearnorm=-4,logtopsum=8)
g$pvalue