Statistics::Descriptive - Module of basic descriptive statistical functions. River stage two • 23 direct dependents • 39 total dependents 18 ++

This module provides basic functions used in descriptive statistics. It has an object oriented design and supports two different types of data storage and calculation objects: sparse and full. With the sparse method, none of the data is stored and on...

/Statistics-Descriptive-3.0800 - 17 Oct 2020 08:36:07 UTC

Statistics::Descriptive::Full - Module of basic descriptive statistical functions. River stage two • 23 direct dependents • 39 total dependents 18 ++

This module provides basic functions used in descriptive statistics. It has an object oriented design and supports two different types of data storage and calculation objects: sparse and full. With the sparse method, none of the data is stored and on...

/Statistics-Descriptive-3.0800 - 17 Oct 2020 08:36:07 UTC

Statistics::Descriptive::Sparse - Module of basic descriptive statistical functions. River stage two • 23 direct dependents • 39 total dependents 18 ++

This module provides basic functions used in descriptive statistics. It has an object oriented design and supports two different types of data storage and calculation objects: sparse and full. With the sparse method, none of the data is stored and on...

/Statistics-Descriptive-3.0800 - 17 Oct 2020 08:36:07 UTC

Statistics::Descriptive::LogScale - Memory-efficient approximate univariate descriptive statistics class. River stage zero No dependents ++

This module aims at providing some advanced statistical functions without storing all data in memory, at the cost of certain (predictable) precision loss. Data is represented by a set of bins that only store counts of fitting data points. Most bins a...

/Statistics-Descriptive-LogScale-0.11 - 11 Nov 2017 22:52:08 UTC

Statistics::Descriptive::Weighted - Module of basic descriptive statistical functions for weighted variates. River stage zero No dependents 1 ++

This module partially extends the module Statistics::Descriptive to handle weighted variates. Like that module, this module has an object-oriented design and supports two different types of data storage and calculation objects: sparse and full. With ...

/Statistics-Descriptive-Weighted-0.7 - 04 Apr 2014 00:04:43 UTC

Statistics::Descriptive::Smoother - Base module for smoothing statistical data River stage two • 23 direct dependents • 39 total dependents 18 ++

This module provide methods to smooth the trend of a series of statistical data. The methods provided are the "Exponential" and the "Weighted Exponential" (see respectively "Statistics::Descriptive::Smoother::Exponential" and "Statistics::Descriptive...

/Statistics-Descriptive-3.0800 - 17 Oct 2020 08:36:07 UTC

Statistics::Descriptive::Discrete - Compute descriptive statistics for discrete data sets. River stage zero No dependents 1 ++

This module provides basic functions used in descriptive statistics. It borrows very heavily from Statistics::Descriptive::Full (which is included with Statistics::Descriptive) with one major difference. This module is optimized for discretized data ...

/Statistics-Descriptive-Discrete-0.12 - 05 May 2019 05:18:26 UTC

Statistics::Descriptive::Smoother::Exponential - Implement exponential smoothing River stage two • 23 direct dependents • 39 total dependents 18 ++

This module implement the exponential smoothing algorithm to smooth the trend of a series of statistical data. This algorithm works well for unsmoothed data build with big number of samples. If this is not the case you might consider using the "Weigh...

/Statistics-Descriptive-3.0800 - 17 Oct 2020 08:36:07 UTC

Statistics::Descriptive::Smoother::Weightedexponential - Implement weighted exponential smoothing River stage two • 23 direct dependents • 39 total dependents 18 ++

This module implement the weighted exponential smoothing algorithm to smooth the trend of a series of statistical data. This algorithm can help to control large swings in the unsmoothed data that arise from small samples for those data points. The al...

/Statistics-Descriptive-3.0800 - 17 Oct 2020 08:36:07 UTC

Statistics::Running - Basic descriptive statistics (mean/stdev/min/max/skew/kurtosis) and discrete Probability Distribution (via histogram) over data without the need to store data points ever. OOP style. River stage zero No dependents ++

Statistics are updated every time a new data point is added in. The common practice to calculate descriptive statistics for 5 data points as well as 1 billion points is to store them in an array, loop over the array to calculate the mean, then loop o...

/Statistics-Running-0.13 - 16 Feb 2019 19:22:25 UTC

Statistics::OLS - perform ordinary least squares and associated statistics, v 0.07. River stage zero No dependents ++

I wrote Statistics::OLS to perform Ordinary Least Squares (linear curve fitting) on two dimensional data: y = a + bx. The other simple statistical module I found on CPAN (Statistics::Descriptive) is designed for univariate analysis. It accomodates OL...

/Statistics-OLS-0.07 - 13 Oct 2000 05:53:44 UTC

Statistics::Cluto - Perl binding for CLUTO River stage zero No dependents ++

This is a perl binding for CLUTO. Please refer to the CLUTO's manual sections 5.6 - 5.8 for details of each function. Basically, Statistics::Cluto has all corresponding methods for functions described in the manual. loading matrix Initial matrix can ...

/Statistics-Cluto-0.01 - 14 Mar 2007 14:07:55 UTC

Statistics::TTest - Perl module to perform T-test on 2 independent samples Statistics::TTest::Sufficient - Perl module to perfrom T-Test on 2 indepdent samples using sufficient statistics River stage one • 3 direct dependents • 3 total dependents ++

Statistics::TTest This is the Statistical T-Test module to compare 2 independent samples. It takes 2 array of point measures, compute the confidence intervals using the PointEstimation module (which is also included in this package) and use the T-sta...

/Statistics-TTest-1.1.0 - 24 Jul 2003 05:33:16 UTC

Statistics::Frequency - simple counting of elements River stage one • 2 direct dependents • 2 total dependents 1 ++

Statistics::Frequency is a simple class for counting *elements*, in other words, their *frequencies*. Note that Statistics::Frequency is not similar to statistics modules like, say, Statistics::Descriptive. Statistics::Frequency doesn't operate on nu...

/Statistics-Frequency-0.04 - 25 Aug 2015 02:57:39 UTC

Statistics::Histogram - Create a standard histogram for command-line display River stage one • 1 direct dependent • 1 total dependent 1 ++

This module exports a single routine, get_histogram, which expects an array reference as its only required argument. The array should contain a sequence of numbers, and the response will be an ascii-formatted histogram, including some header lines pr...

/Statistics-Histogram-0.2 - 08 Jan 2011 22:52:01 UTC

Statistics::Table::F - Perl module for computing the statistical F-ratio River stage zero No dependents ++

See Orwant, Hietaniemi, and Macdonald, *Mastering Algorithms in Perl*, O'Reilly 1999. From Chapter 15: The significance tests covered so far can only pit one group against another. Sure, we could do a t-test of every possible pair of web design firms...

/Statistics-Table-F-0.02 - 18 Oct 1999 18:28:07 UTC

Statistics::Table::F - Perl module for computing the statistical F-ratio River stage zero No dependents ++

See Orwant, Hietaniemi, and Macdonald, *Mastering Algorithms in Perl*, O'Reilly 1999. From Chapter 15: The significance tests covered so far can only pit one group against another. Sure, we could do a t-test of every possible pair of web design firms...

/Statistics-Table-F-0.02 - 18 Oct 1999 18:28:07 UTC

Statistics::LSNoHistory - Least-Squares linear regression package without data history River stage zero No dependents ++

This package provides standard least squares linear regression functionality without the need for storing the complete data history. Like any other, it finds best m,k (in least squares sense) so that y = m*x + k fits data points (x_1,y_1),...,(x_n,y_...

/Statistics-LSNoHistory-0.01 - 02 Mar 2003 03:07:24 UTC

Statistics::Running::Tiny - Basic descriptive statistics (mean/stdev/min/max/skew/kurtosis) over data without the need to store data points ever. OOP style. River stage zero No dependents 1 ++

Calculate basic descriptive statistics (mean, variance, standard deviation, skewness, kurtosis) without the need to store any data point/sample. Statistics are updated each time a new data point/sample comes in. There are three amazing things about B...

/Statistics-Running-Tiny-0.03 - 16 Feb 2019 19:23:53 UTC

Statistics::FisherPitman - Randomization-based alternative to one-way independent groups ANOVA; unequal variances okay River stage zero No dependents ++

Tests for a difference between independent samples. It is commonly recommended as an alternative to the oneway independent groups ANOVA when variances are unequal, as its test-statistic, *T*, is not dependent on an estimate of variance. As a randomiz...

/Statistics-FisherPitman-0.034 - 12 Sep 2010 08:41:08 UTC
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