Last data update: 2014.03.03

R: Probability that the Greenwood's statistic is smaller than...
pGreenwood1R Documentation

Probability that the Greenwood's statistic is smaller than one

Description

Probability that the Greenwood's statistic is smaller than one.

Usage

 
   pGreenwood1(n)

Arguments

n

Sample size.

Details

The probability was computed by using the approximation of the quantile function of the Greenwood's statistic returned by qStat. The result is found by interpolating the distribution function for x = 1.

Value

Probability that the Greenwood's statistic is smaller than one. For a random sample of an exponential distribution with size n, this is the probability that the coefficient of variation is less than one, or the probability that the ML estimate of the GPD shape parameter ξ is negative.

Author(s)

Yves Deville

Examples

n <- 8:500
plot(n, pGreenwood1(n), type = "l", col = "orangered", lwd = 2,
     log ="x", ylim =c(0.5, 0.7), main = "slow convergence to 0.5")
grid() ; abline(h = 0.5, col = "SpringGreen")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(Renext)
Loading required package: evd
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Renext/pGreenwood1.Rd_%03d_medium.png", width=480, height=480)
> ### Name: pGreenwood1
> ### Title: Probability that the Greenwood's statistic is smaller than one
> ### Aliases: pGreenwood1
> 
> ### ** Examples
> 
> n <- 8:500
> plot(n, pGreenwood1(n), type = "l", col = "orangered", lwd = 2,
+      log ="x", ylim =c(0.5, 0.7), main = "slow convergence to 0.5")
> grid() ; abline(h = 0.5, col = "SpringGreen")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>