com.datumbox.framework.core.statistics.sampling

Class StratifiedSampling

java.lang.Object

com.datumbox.framework.core.statistics.sampling.StratifiedSampling

public class StratifiedSampling
extends java.lang.Object

This class provides methods which can be used for performing Stratified Sampling.

Constructor Summary

Constructors

Constructor and Description
StratifiedSampling()

Method Summary

Modifier and Type	Method and Description
static double	mean(TransposeDataCollection sampleDataCollection, AssociativeArray populationNh) Calculate the mean from the sample
static AssociativeArray	optimumSampleSize(int n, AssociativeArray populationNh, AssociativeArray populationStdh) Returns the optimum sample size per strata under Neyman Allocation
static TransposeDataCollection	randomSampling(TransposeDataList strataIdList, AssociativeArray nh, boolean withReplacement) Samples nh ids from each strata by using Stratified Sampling
static double	std(TransposeDataCollection sampleDataCollection, AssociativeArray populationNh) Calculate the standard deviation of the sample
static double	variance(TransposeDataCollection sampleDataCollection, AssociativeArray populationNh) Calculate the variance from the sample
static TransposeDataCollection	weightedProbabilitySampling(AssociativeArray2D strataFrequencyTable, AssociativeArray nh, boolean withReplacement) Samples nh ids from each strata based on their Frequency Table
static double	xbarStd(TransposeDataCollection sampleDataCollection, AssociativeArray nh, AssociativeArray populationNh) Calculates Standard Deviation for Xbar
static double	xbarVariance(TransposeDataCollection sampleDataCollection, AssociativeArray nh, AssociativeArray populationNh) Calculates Variance for Xbar

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

StratifiedSampling

public StratifiedSampling()

Method Detail

weightedProbabilitySampling

public static TransposeDataCollection weightedProbabilitySampling(AssociativeArray2D strataFrequencyTable,
                                                                  AssociativeArray nh,
                                                                  boolean withReplacement)

Samples nh ids from each strata based on their Frequency Table

Parameters:

strataFrequencyTable -

nh -

withReplacement -

Returns:

randomSampling

public static TransposeDataCollection randomSampling(TransposeDataList strataIdList,
                                                     AssociativeArray nh,
                                                     boolean withReplacement)

Samples nh ids from each strata by using Stratified Sampling

Parameters:

strataIdList -

nh -

withReplacement -

Returns:

mean

public static double mean(TransposeDataCollection sampleDataCollection,
                          AssociativeArray populationNh)

Calculate the mean from the sample

Parameters:

sampleDataCollection -

populationNh -

Returns:

variance

public static double variance(TransposeDataCollection sampleDataCollection,
                              AssociativeArray populationNh)

Calculate the variance from the sample

Parameters:

sampleDataCollection -

populationNh -

Returns:

std

public static double std(TransposeDataCollection sampleDataCollection,
                         AssociativeArray populationNh)

Calculate the standard deviation of the sample

Parameters:

sampleDataCollection -

populationNh -

Returns:

xbarVariance

public static double xbarVariance(TransposeDataCollection sampleDataCollection,
                                  AssociativeArray nh,
                                  AssociativeArray populationNh)

Calculates Variance for Xbar

Parameters:

sampleDataCollection -

nh -

populationNh -

Returns:

xbarStd

public static double xbarStd(TransposeDataCollection sampleDataCollection,
                             AssociativeArray nh,
                             AssociativeArray populationNh)

Calculates Standard Deviation for Xbar

Parameters:

sampleDataCollection -

nh -

populationNh -

Returns:

optimumSampleSize

public static AssociativeArray optimumSampleSize(int n,
                                                 AssociativeArray populationNh,
                                                 AssociativeArray populationStdh)

Returns the optimum sample size per strata under Neyman Allocation

Parameters:

n -

populationNh -

populationStdh -

Returns: