klefsjo.ifra.mc: Function to compute the Monte Carlo P-value for the observed...

Description Usage Arguments Value Author(s) Examples

Description

This is the Monte Carlo approximation to the function "klefsjo.ifra".

Usage

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klefsjo.ifra.mc(x, alternative = "two.sided", exact=FALSE,
                min.reps = 100, max.reps = 1000, delta = 10^-3)

Arguments

x

a vector of data of length n

alternative

the direction of the alternative hypothesis. The choices are two.sided, ifra and dfra with the default value being two.sided.

exact

TRUE/FALSE value that determines whether the exact test or the large sample approximation is used if n >= 9. If n < 9 the exact test is used. The default value is FALSE, so the large sample approximation will be used unless specified not to. This is the same large sample approximation as epstein()

min.reps

the minimum number of repetitions for the Monte Carlo Approximation

max.reps

the maximum number of reps for the Monte Carlo Approximation. If the maximum number of reps has been reached, and the probability has not converged, a warning is given.

delta

the measure of accuracy for the convergence. If the probability converges to within delta, the Monte Carlo procedure stops before reaching the maximum number of reps.

Value

The function returns a list with two elements:

B.star

the value of the Klefsjo statistic

p

the corresponding probability

Author(s)

Rachel Becvarik

Examples

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temp.data<-c(0.33925023, 0.84005767, 0.29066189, 1.95163010, 0.74536608, 0.16714902, 0.06950791, 
1.14919291,1.93210982, 1.06006126, 0.14651009, 0.28776282, 0.72242750, 1.02227211, 1.71243334)
klefsjo.ifra.mc(temp.data, exact=TRUE)

NSM3 documentation built on April 6, 2021, 5:05 p.m.

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