gs.siem.sample.test: Estimator Sample Test

In neurodata/graphstats: Graph Statistics

Description

A function that computes the p value of falsely rejecting H0 that x_i !? x_j in favor of HA that x_j ? x_i for x_i, x_j from the same sample.

Usage

gs.siem.sample.test(x1, x2, var1, var2, df = NULL, n1 = NULL, n2 = NULL,
  alt = "greater")

Arguments

x1	expectation value of an estimator.
x2	expectation value of a second estimator.
var1	the variance of the first estimator.
var2	the variance of the second estimator.
df=NULL	the number of degrees of freedom involved. Ignored if n1 and n2 are provided.
n1=NULL	the number of observations for the first estimator. If n1 and n2 are not provided, the number of degrees of freedom is set to df.
n2=NULL	the number of observations for the second estimator. If n1 and n2 are not provided, the number of degrees of freedom is set to df. 1x1 and x2 are from different samples 2x1 and x2 are from different samples
alt='greater'	the alternative hypothesis for each edge test. 'greater'p corresponds to H0: x1 <= x2, HA: x1 > x2. R(x1, x2) = x1 > x2 'neq'p corresponds to H0: x1 = x2, HA: x1 != x2. R(x1, x2) = x1 != x2 'less'p corresponds to H0: x1 >= x2, HA: x1 < x2. R(x1, x2) = x1 < x2

Value

p is the p-value of false rejection of H0 that !R(x1, x2) in favor of HA that R(x1, x2).

neurodata/graphstats documentation built on May 14, 2019, 5:19 p.m.