pi.science.api
1.2.6
Scientific library.
See the version list below for details.
InstallPackage pi.science.api Version 1.2.6
dotnet add package pi.science.api version 1.2.6
<PackageReference Include="pi.science.api" Version="1.2.6" />
paket add pi.science.api version 1.2.6
PI Science API
Scientific library for .NET (standard 2.0).
Supported areas:
 Statistics (descriptive statistics, statistics classes) .
 Math (matrices, Cramer`s rule, Gamma function, Beta function, Error function,
Gamma incomplete function, numerical integrationTrapezoidal rule, numerical integrationRectangle rule,
numerical integrationSimpsons rule).  Discrete math (primes, prime factorization, prime factorizationFermat).
 Probability (factorial, combination, Catalan number).
 Regression (linear, polynomial, exponential, exponential modified, power, Gompertz, logistic).
 Smoothing (moving average, median smoothing, simple exponential smoothing, double exponential smoothing).
 Probability distribution (normal distribution, chisquare distribution, students distribution, f distribution, lognormal distribution, exponential distribution,
Poisson distribution, Erlang distribution, Weibull distribution, Rayleigh distribution, Pareto distribution).  Hypothesis testing (ShapiroWilk(original), ShapiroWilk(expanded), Skewness normality test, Kurtosis normality test, D`AgostinoPearson normality test, JarqueBera normality test).
Examples
Examples for every area you can find here.
HTML documentation included (for download here.).
TEST classes you can download here.
Scheduled areas for next development:
Integrals, correlations, interpolations, hypothesis testing, fractions support, neural networks, graph algorithms, cluster analysis...
PI Science API
Scientific library for .NET (standard 2.0).
Supported areas:
 Statistics (descriptive statistics, statistics classes) .
 Math (matrices, Cramer`s rule, Gamma function, Beta function, Error function,
Gamma incomplete function, numerical integrationTrapezoidal rule, numerical integrationRectangle rule,
numerical integrationSimpsons rule).  Discrete math (primes, prime factorization, prime factorizationFermat).
 Probability (factorial, combination, Catalan number).
 Regression (linear, polynomial, exponential, exponential modified, power, Gompertz, logistic).
 Smoothing (moving average, median smoothing, simple exponential smoothing, double exponential smoothing).
 Probability distribution (normal distribution, chisquare distribution, students distribution, f distribution, lognormal distribution, exponential distribution,
Poisson distribution, Erlang distribution, Weibull distribution, Rayleigh distribution, Pareto distribution).  Hypothesis testing (ShapiroWilk(original), ShapiroWilk(expanded), Skewness normality test, Kurtosis normality test, D`AgostinoPearson normality test, JarqueBera normality test).
Examples
Examples for every area you can find here.
HTML documentation included (for download here.).
TEST classes you can download here.
Scheduled areas for next development:
Integrals, correlations, interpolations, hypothesis testing, fractions support, neural networks, graph algorithms, cluster analysis...
Release Notes
+ Added new class pi.science.hypothesistesting.PIKurtosisTest.
+ Added new test class pi.science.hypothesistesting.test.PIKurtosisTestTest.
+ Added new method pi.statistics.api.PIVariable.GetSampleKurtosis()  (Excel version).
+ Added new namespace pi.science.ai.
+ Added new class pi.science.hypothesistesting.PIDAgostinoPearson.
+ Added new test class pi.science.hypothesistesting.test.PIDAgostinoPearsonTest.
+ Added new method pi.statistics.api.PIVariable.SaveToFile().
+ Added new method pi.statistics.api.PIValue.GetValueStr().
+ Added new class pi.science.hypothesistesting.PIJarqueBera.
+ Added new test class pi.science.hypothesistesting.test.PIJarqueBeraTest.
+ Added new method pi.statistics.api.PIVariable.GetKurtosisJarqueBera().
Dependencies

.NETStandard 2.0
 No dependencies.
Used By
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.