nuget
The statistics library root: descriptive statistics, hypothesis testing and statistical resampling.
Microsoft.VisualBasic.Math.Statistics 1.0.9762.11310.
01 Namespaces
Microsoft.VisualBasic.Math.Statistics
| Type | Summary | Members |
|---|---|---|
| ChiSquareTest | 20 | |
| Extensions | 1 | |
| FastICA | FastICA (Fast Independent Component Analysis) implementation. | 76 |
| FisherTest | Fisher's exact test > https://en.wikipedia.org/wiki/Fisher's_exact_test Fisher 's exact test is a statistical significance test used in the analysis of contingency tables.[… | 5 |
| FTest | 8 | |
| LogLikelihood | calculates log likelihood between a source and a reference corpus. | 1 |
| SpecialFunctions | @author Will_and_Sara | 24 |
Microsoft.VisualBasic.Math.Statistics.Distributions
Statistical distributions and their parameter estimation.
| Type | Summary | Members |
|---|---|---|
| ContinuousDistribution | @author Will_and_Sara | 10 |
| Distribution | 21 | |
| Skellam | Skellam 分布：两个独立 Poisson 变量之差 X = Y1 - Y2 的分布 （Y1 ~ Poisson(lambda1)，Y2 ~ Poisson(lambda2)）。 本模块移植自 R 语言的 skellam 包 （参见项目 Resources\pskellam.txt、Resources\dskellam.txt、 Resour… | 11 |
Microsoft.VisualBasic.Math.Statistics.Distributions.LinearMoments
Distribution parameter estimation through linear moments (L-moments).
| Type | Summary | Members |
|---|---|---|
| Exponential | @author Will_and_Sara | 4 |
| GEV | @author Will_and_Sara and Micheal Wright | 4 |
| Gumbel | @author Will_and_Sara | 4 |
| Logistic | @author Will_and_Sara | 4 |
| LogPearsonIII | @author Will_and_Sara | 4 |
| Pareto | @author Will_and_Sara | 5 |
Microsoft.VisualBasic.Math.Statistics.Distributions.MethodOfMoments
Distribution parameter estimation through the method of moments.
| Type | Summary | Members |
|---|---|---|
| Beta | @author Will_and_Sara | 4 |
| Emperical | @author Will_and_Sara | 4 |
| Exponential | @author Will_and_Sara | 4 |
| Gamma | @author Will_and_Sara | 4 |
| GEV | @author Will_and_Sara | 4 |
| Gumbel | @author Will_and_Sara | 4 |
| LogNormal | @author Will_and_Sara | 6 |
| LogPearsonIII | @author Will_and_Sara | 5 |
| Normal | normal distribution @author Will_and_Sara | 9 |
| Rayleigh | @author Will_and_Sara | 5 |
| Triangular | @author Will_and_Sara | 7 |
| Uniform | @author Will_and_Sara | 6 |
Microsoft.VisualBasic.Math.Statistics.Hypothesis
Statistical hypothesis testing procedures.
| Type | Summary | Members |
|---|---|---|
| Hypothesis | 6 | |
| MoranTest | 9 | |
| NullHypothesis | 4 | |
| t | Performs one and two sample t-tests on vectors of data. | 5 |
| Topt | 4 | |
| TtestResult | 11 |
Microsoft.VisualBasic.Math.Statistics.Hypothesis.FishersExact
Fisher's exact test for contingency tables.
| Type | Summary | Members |
|---|---|---|
| FishersExactPvalues | FishersExactPvalues holds the pvalues calculated by the fishers_exact function. | 6 |
| FishersExactTest | Fisher's exact test. Implements a 2×2 Fishers exact test. Use this to test the independence of two categorical variables when the sample sizes are small. For an approachable e… | 7 |
Microsoft.VisualBasic.Math.Statistics.Hypothesis.Mantel
The Mantel test for correlation between distance matrices.
| Type | Summary | Members |
|---|---|---|
| corr | 2 | |
| Model | the test model | 6 |
| Result | 4 | |
| statistical_test | 6 | |
| stats | 13 |
Microsoft.VisualBasic.Math.Statistics.Hypothesis.Mantel.corr
| Type | Summary | Members |
|---|---|---|
| corr | An abstract delegate function for measure the correlation between two given numeric vector | 3 |
Microsoft.VisualBasic.Math.Statistics.MomentFunctions
Statistical moment functions (mean, variance, skewness, kurtosis and related measures).
| Type | Summary | Members |
|---|---|---|
| BasicProductMoments | 可以利用这个模块来进行一组数据的正态分布的参数的估计 @author Will_and_Sara | 9 |
| BasicProductMomentsHistogram | @author Will_and_Sara | 0 |
| LinearMoments | @author Will_and_Sara | 10 |
| ProductMoments | In statistics, moments are a set of numerical characteristics that describe the shape and features of a probability distribution. | 18 |
Microsoft.VisualBasic.Math.Statistics.RANSAC
The RANSAC (random sample consensus) robust model fitting algorithm.
| Type | Summary | Members |
|---|---|---|
| Algorithm | RANSAC (RANdom SAmple Consensus) is an algorithm for measuring system parameters for some input data. | 1 |
Microsoft.VisualBasic.Math.Statistics.ShapleyValue
Shapley value computation for feature attribution.
| Type | Summary | Members |
|---|---|---|
| CharacteristicFunction | represent the following function often written by v 2^N to R for each subset of the set {1.. | 4 |
| CoalitionStrategy | @author Franck Benault @version 0.0.2 @since 0.0.2 | 8 |
| IShapExplainer | The unified contract of a SHAP explainer. | 4 |
| LinearShapExplainer | 线性（以及广义线性）模型的解析 SHAP 解释器。 对于线性模型 f(x) = b0 + sum(bi * xi)，在背景分布之上关于特征 i 的 精确 Shapley 值为：phi_i = bi * (xi - E[xi])， 而基线值为 b0 + sum(bi * E[xi])。 因此 sum(phi) + baseline = f(x)… | 11 |
| ShapExplanation | 单个样本的 SHAP 解释结果。 | 10 |
| ShapleyApplication | facade of Shapley application @author Franck Benault @version 0.0.2 @since 0.0.2 | 4 |
| TreeShapExplainer | 基于 TreeSHAP 算法（论文 arXiv:1802.03888）的树集成 SHAP 解释器。 该解释器把多棵 PkTree 的逐特征贡献相加， 并且把所有树的期望值（cover 加权叶值均值）与一个常数偏置项 （TreeShapExplainer.Intercept，例如梯度提升模型的 base score）相加作为最终的基线值。 因此… | 9 |
Microsoft.VisualBasic.Math.Statistics.ShapleyValue.TreeShap
The TreeSHAP algorithm for Shapley value based tree model interpretation.
| Type | Summary | Members |
|---|---|---|
| PathElement | Path element for use in ShapAlgo2 | 9 |
| PkNode | 16 | |
| PkTree | 3 | |
| ShapAlgo1 | See https://arxiv.org/pdf/1802.03888.pdf - Chapter 3.1, Algorithm 1. | 8 |
| ShapAlgo2 | Rewrite of the Algorithm 2 from [1]. | 3 |
| ShapOptimized | 8 |