search.best.n.bisection: Method of bisection for estimating optimal sample size

In hscovar: Calculation of Covariance Between Markers for Half-Sib Families

Description

A grid [nstart, nmax] for possible sample size is considered. Instead of executing a time-consuming grid search, the method of bisection is applied to this interval. For each step, the function pwr.normtest is called for the given set of parameters.

Usage

search.best.n.bisection(
  R,
  betaSE,
  lambda,
  pos,
  nstart,
  nmax,
  weights = 1,
  typeII = 0.2,
  alpha = 0.01
)

Arguments

R	(p x p) matrix containing theoretical correlation between SNP pairs
betaSE	effect size relative to residual standard deviation
lambda	shrinkage parameter
pos	vector (LEN nqtl) of SNP indices for assumed QTL positions
nstart	minimum value for grid search
nmax	maximum value for grid search
weights	vector (LEN p) of SNP-specific weights or scalar if weights are equal for all SNPs; default value 1
typeII	type-II error level; default value 0.2
alpha	type-I error level; default value 0.01

Value

integer of optimal sample size

Examples

  ### correlation matrix (should depend on sire haplotypes)
  R <- AR1(100, rho = 0.1)
  ### positions of putative QTL signals
  pos <- c(14, 75)
  ### optimal sample size
  search.best.n.bisection(R, 0.35, 1200, pos, 10, 5000)

hscovar documentation built on April 13, 2021, 9:06 a.m.