Probability And Statistics For .net
This suite consists of six packages: Statistics, Discrete Probability, Standard Probability Distributions, Curve Fitting, Hypothesis Testing, and Correlation & Regression which offer the following functionality.
The Statistics module incorporates topic from data presentation (incl. standard, relative and cumulative frequency tables), Basic Statistics (incl. measure of centrality, dispersion and relative location), Grouped Data (incl. Sample Mean, Variance and Standard Deviation) and Quality Control(incl. R-Chart, S-Chart and Median Chart).
Discrete Probability Module
The Discrete Probability module encapsulates the probabilistic study of finite set of events (i.e. discrete probability) and experiments with a finite number of outcomes (i.e. discrete random variables). Including: probability measures, union/intersection law, conditionals/complementary probability; cumulative distribution functions, mean/variance/expected return of Random Variable.
Standard Probability Distributions Module
This module assists in the development of applications that incorporate the Binomial, Poisson, Normal, Lognormal, Pareto, Uniform, Hypergeometric, Weibull and Exponential probability distributions. The probability density function, cumulative distribution function and inverse, mean, variance, Skewness and Kurtosis are implemented where appropriate and/or their approximations for each distribution. We also offer methods which randomly generate numbers from a given distribution.
Allows the fitting of linear and non-linear functions for a data set which may or may not exhibit measurement errors in accordance with the least squares approach. A general linear algorithm and the specialized Levenberg-Marquardt algorithm to handle the non-linear case are provided. We also include functionality which performs ANNOVA type analysis including goodness-of-fit measures such as the R-Squared measure and T-Test statistic.
Confidence Intervals and Hypothesis Testing Module
Within this component we present two aspects of inferential statistics known as confidence intervals and hypothesis testing. Confidence intervals determine the level of confidence in pointwise statistics (e.g. mean, variance) of the sample in relation to the statistics for the entire population. With hypothesis testing the user can judge which of several hypotheses sampled evidence best supports.
Correlation and Regression Module
Allows the user to investigate relationships between two variables. These finding can be used to predict one variable from the given values of other variables. We cover linear (Spearman's, t-test, z-transform) and rank (Spearman's, Kendall's) correlation, linear regression and conditional means.
It can perform a one or two sided test.The script outputs the probability of observing the resulting value of "s" or "a" value, given "n" total outcom...
Functions for Rice/Rician PDF, mean and variance, and generating random samples.Similar to e.g. normpdf, normrnd, normstat from the MATLAB statistics ...
ENTROPY(X,P) returns the (joint) entropy for the joint distribution corresponding to object matrix X and probability vector P. Each row of MxN matrix ...
A pair of files for calculating Cochran statistics.The file COCH_INV.M calculates the Cochran's critical values themselves. The file ACOCHINV.M return...
Phpbb Statistics 1.0.2
A special option is added to the front page menu and the Administration Control Panel. Here are some key features of "phpBB Statistics":· Basic f...
Probability Of Error For M-array Orthogonal Signal
The attached Matlab file estimate numerically the probability of error for M-array orthogonal signals and plot the graph BER for M-signals [2 to 64].N...
There programs are very useful for simple statistical tests.t_confidence_interval calculates the confidence interval of the t-distrubution, with one o...
Implied Default Probability Function
This function is to calculate the implied default probability from the DOC model. Source: Brockman and Turtle (2003).> Default probability (%)> Bar...
General Viterbi Algorithm
General implementation of matlab version of Viterbi algorithm was specifically written for gene structure finding problem. However, it can be mod...
JS does not natively support probabilities. Probability.js adds support for such term/concept, allowing developers to use common probable logic when p...
There are three parts to this library of routines.1. *[rnd,pdf,lpr].m - distribution function tools to complement MATLAB's2. mcmc*.m - routines to cal...
ecdfcalc4fe calculates absic statistics for a sample set: mean, variance, std.dev, kurtosis, skewness, probability mass function/density funcion and c...
Erdos-renyi Random Graph
The Erdos-Renyi (Erdos and Renyi, 1959) is the first ever proposed algorithm for the formation of random graphs. It selects with equal probability pai...
Implements the static behaviours of the Stat Class, which deals with Probability and Statistics math algorithms.usage:Stat.classMethod(args);...
Statistical Dependence Index
function [argout1 argout2 argout3 argout4]=sdindex2(data,threshold)calculation of statistical dependence indexINPUTSdata: a two column matrix, each co...
Ruby Stats is a port of the statistics libraries from PHPMath.Probability distributions include binomial, beta, and normal distributions with PDF, CDF...
function [pdffit,offset,A,B,resnorm,h] = distributionfit(data,distribution,nbins)PURPOSE jdc rev. 06-jun-05Fit one of three probability distributions ...
Bivariate Cumulative Normal Probability
bivnormcdf gives the bivariate normal probability.function p = bivnormcdf(a,b,rho)where rho is the correlation. Requirements:· MATLAB Release: R1...
The Hardy Weinberg equilibrium is a fundamental law in genetic. Often a locus shows multiple alleles with low frequency, so the application of chi squ...
This application is an IRC Statistics Bot written in Perl. It logs its statistics to a mysql database, and it features a web interface for these stati...