ParaMonte Fortran 2.0.0 Parallel Monte Carlo and Machine Learning LibrarySee the latest version documentation.
pm_sampleQuan Module Reference

This module contains procedures and data types for computing sample quantile.
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## Data Types

interface  getQuan
Generate and return the approximate sample quantile for the given method at the specified probabilities. More...

## Variables

character(*, SK), parameter MODULE_NAME = "@pm_sampleQuan"

## Detailed Description

This module contains procedures and data types for computing sample quantile.

Quantiles are cut points dividing the range of a probability distribution into continuous intervals with equal probabilities, or dividing the observations in a sample in the same way.
There is one fewer quantile than the number of groups created.
Common quantiles have special names, such as quartiles (four groups), deciles (ten groups), and percentiles (100 groups).
The groups created are termed halves, thirds, quarters, etc., though sometimes the terms for the quantile are used for the groups created, rather than for the cut points.

Q-quantiles are values that partition a finite set of values into $$q$$ subsets of (nearly) equal sizes.
There are $$q − 1$$ partitions of the $$q$$-quantiles, one for each integer $$k$$ satisfying $$0 < k < q$$.
In some cases the value of a quantile may not be uniquely determined, as can be the case for the median ( $$2$$-quantile) of a uniform probability distribution on a set of even size.
Quantiles can also be applied to continuous distributions, providing a way to generalize rank statistics to continuous variables.
When the cumulative distribution function of a random variable is known, the $$q$$-quantiles are the application of the quantile function (the inverse function of the cumulative distribution function) to the values $$\{1/q, 2/q, …, (q − 1)/q\}$$.

pm_sampling
pm_sampleACT
pm_sampleCCF
pm_sampleCor
pm_sampleCov
pm_sampleConv
pm_sampleECDF
pm_sampleMean
pm_sampleNorm
pm_sampleQuan
pm_sampleScale
pm_sampleShift
pm_sampleWeight
pm_sampleAffinity
pm_sampleVar
pm_polation
Test:
test_pm_sampleQuan

Final Remarks

If you believe this algorithm or its documentation can be improved, we appreciate your contribution and help to edit this page's documentation and source file on GitHub.

1. If you use any parts or concepts from this library to any extent, please acknowledge the usage by citing the relevant publications of the ParaMonte library.
2. If you regenerate any parts/ideas from this library in a programming environment other than those currently supported by this ParaMonte library (i.e., other than C, C++, Fortran, MATLAB, Python, R), please also ask the end users to cite this original ParaMonte library.

This software is available to the public under a highly permissive license.
Help us justify its continued development and maintenance by acknowledging its benefit to society, distributing it, and contributing to it.

Author:
Amir Shahmoradi, Tuesday March 7, 2017, 3:50 AM, Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin

## ◆ MODULE_NAME

 character(*, SK), parameter pm_sampleQuan::MODULE_NAME = "@pm_sampleQuan"

Definition at line 74 of file pm_sampleQuan.F90.