randomOrderNormal

Generates pseudorandom order statistics from a standard normal distribution.

Synopsis

randomOrderNormal (ifirst, ilast, n)

Required Arguments

int ifirst (Input)

First order statistic to generate.

int ilast (Input)

Last order statistic to generate.

ilast must be greater than or equal to ifirst. The full set of order statistics from ifirst to ilast is generated. If only one order statistic is desired, set ilast = ifirst.

int n (Input)

Size of the sample from which the order statistics arise.

Return Value

An array of length ilast + 1 - ifirst containing the random order statistics in ascending order. The first element is the ifirst order statistic in a random sample of size n from the standard normal distribution.

Description

Function randomOrderNormal generates the ifirst through the ilast order statistics from a pseudorandom sample of size n from a normal (0, 1) distribution. Function randomOrderNormal uses the function randomOrderUniform to generate order statistics from the uniform (0, 1) distribution and then obtains the normal order statistics using the inverse CDF transformation.

Each call to randomOrderNormal yields an independent event so order statistics from different calls may not have the same order relations with each other.

Example

In this example, randomOrderNormal is used to generate the fifteenth through the nineteenth order statistics from a sample of size twenty.

from __future__ import print_function
from numpy import *
from pyimsl.stat.randomOrderNormal import randomOrderNormal
from pyimsl.stat.randomSeedSet import randomSeedSet
from pyimsl.stat.writeMatrix import writeMatrix


randomSeedSet(123457)
r = randomOrderNormal(15, 19, 20)
print("The 15th through the 19th order statistics from a \n",
      "random sample of size 20 from a normal distribution")
writeMatrix("", r, column=True)

Output

The 15th through the 19th order statistics from a 
 random sample of size 20 from a normal distribution
 
1       0.4056
2       0.4681
3       0.4697
4       0.9067
5       0.9362