TYoshimura.DoubleDouble.Statistic 1.4.1

.NET 8.0 This package targets .NET 8.0. The package is compatible with this framework or higher.
There is a newer version of this package available.
See the version list below for details. 
dotnet add package TYoshimura.DoubleDouble.Statistic --version 1.4.1
                    


                    

                
NuGet\Install-Package TYoshimura.DoubleDouble.Statistic -Version 1.4.1
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package. 
<PackageReference Include="TYoshimura.DoubleDouble.Statistic" Version="1.4.1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
<PackageVersion Include="TYoshimura.DoubleDouble.Statistic" Version="1.4.1" />
                    


                            Directory.Packages.props
                        

                    

                
<PackageReference Include="TYoshimura.DoubleDouble.Statistic" />
                    


                            Project file
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package. 
paket add TYoshimura.DoubleDouble.Statistic --version 1.4.1
                    


                    

                
#r "nuget: TYoshimura.DoubleDouble.Statistic, 1.4.1"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package. 
#:package TYoshimura.DoubleDouble.Statistic@1.4.1
#:package directive can be used in C# file-based apps starting in .NET 10 preview 4. Copy this into a .cs file before any lines of code to reference the package. 
#addin nuget:?package=TYoshimura.DoubleDouble.Statistic&version=1.4.1
                    


                            Install as a Cake Addin
                        

                    

                
#tool nuget:?package=TYoshimura.DoubleDouble.Statistic&version=1.4.1
                    


                            Install as a Cake Tool

DoubleDoubleStatistic

Double-Double Statistic Implements

Requirement

.NET 8.0
DoubleDouble
DoubleDoubleComplex

Install

Download DLL
Download Nuget

Implemented Distributions

Continuous

category distribution PDF CDF quantile statistic fitting random generation note
stable cauchy ✔ ✔ ✔ ✔ ✔ ✔
delta ✔ ✔ ✔ ✔ ✔ ✔
holtsmark ✔ ✔ ✔ ✔ ✔ ✔
landau ✔ ✔ ✔ ✔ ✔ ✔
levy ✔ ✔ ✔ ✔ ✔ ✔
map-airy ✔ ✔ ✔ ✔ ✔ ✔
normal ✔ ✔ ✔ ✔ ✔ ✔
sas point5 ✔ ✔ ✔ ✔ ✔ ✔
linearity cosine ✔ ✔ ✔ ✔ ✔ ✔
davis ✔ ✔ ✔ ✔ ⚠ ⚠ CDF and Quantile take longer to calculate.
frechet ✔ ✔ ✔ ✔ ✔ ✔
gumbel ✔ ✔ ✔ ✔ ✔ ✔
johnson sb ✔ ✔ ✔ ✔ ✔ ✔
johnson su ✔ ✔ ✔ ✔ ✔ ✔
laplace ✔ ✔ ✔ ✔ ✔ ✔
logistic ✔ ✔ ✔ ✔ ✔ ✔
skew normal ✔ ✔ ✔ ✔ ⚠ ⚠ Quantile take longer to calculate.
uniform ✔ ✔ ✔ ✔ ✔ ✔
u quadratic ✔ ✔ ✔ ✔ ✔ ✔
weibull ✔ ✔ ✔ ✔ ✔ ✔
scalable birnbaum saunders ✔ ✔ ✔ ✔ ✔ ✔
exponential ✔ ✔ ✔ ✔ ✔ ✔
folded normal ✔ ✔ ✔ ✔ ✔ ✔
gamma ✔ ✔ ✔ ✔ ✔ ✔
gompertz ✔ ✔ ✔ ✔ ✔ ✔
half normal ✔ ✔ ✔ ✔ ⚠ ⚠ Quantile take longer to calculate.
hyperbolic secant ✔ ✔ ✔ ✔ ✔ ✔
inverse gauss ✔ ✔ ✔ ✔ ⚠ ⚠ Quantile take longer to calculate.
log logistic ✔ ✔ ✔ ✔ ✔ ✔
lomax ✔ ✔ ✔ ✔ ✔ ✔
maxwell ✔ ✔ ✔ ✔ ✔ ✔
pareto ✔ ✔ ✔ ✔ ✔ ✔
rayleigh ✔ ✔ ✔ ✔ ✔ ✔
voigt ✔ ✔ ✔ ✔ ⚠ ⚠ CDF and Quantile take longer to calculate.
wigner semicircle ✔ ✔ ✔ ✔ ✔ ✔
continuous alpha ✔ ✔ ✔ ✔ ✔ ✔
arcsine ✔ ✔ ✔ ✔ - ✔
argus ✔ ✔ ✔ ✔ ⚠ ⚠
benktander ✔ ✔ ✔ ✔ ⚠ ⚠ Quantile take longer to calculate.
beta ✔ ✔ ✔ ✔ ✔ ✔
beta prime ✔ ✔ ✔ ✔ ✔ ✔
bradford ✔ ✔ ✔ ✔ ✔ ✔
burr ✔ ✔ ✔ ✔ ✔ ✔
chi ✔ ✔ ✔ ✔ ✔ ✔
chi square ✔ ✔ ✔ ✔ ✔ ✔
dagum ✔ ✔ ✔ ✔ ✔ ✔
fisher z ✔ ✔ ✔ ✔ ✔ ✔
fisk ✔ ✔ ✔ ✔ ✔ ✔
inverse gamma ✔ ✔ ✔ ✔ ✔ ✔
inverse chi ✔ ✔ ✔ ✔ ✔ ✔
inverse chi sq ✔ ✔ ✔ ✔ ✔ ✔
irwin hall ✔ ✔ ✔ ✔ - ✔ n ≤ 128
kumaraswamy ✔ ✔ ✔ ✔ ✔ ✔
log normal ✔ ✔ ✔ ✔ ✔ ✔
nakagami ✔ ✔ ✔ ✔ ✔ ✔
noncentral chi sq ✔ ✔ ✔ ✔ ❌ ✔ Accuracy decreases when non-centricity is large.
noncentral f ✔ ✔ ✔ ✔ ❌ ✔ Accuracy decreases when non-centricity is large.
noncentral t ✔ ✔ ✔ ✔ ❌ ✔ Accuracy decreases when non-centricity is large.
power ✔ ✔ ✔ ✔ ✔ ✔
reciprocal ✔ ✔ ✔ ✔ ✔ ✔
rice ✔ ✔ ✔ ✔ ⚠ ⚠ CDF and Quantile take longer to calculate.
snedecor f ✔ ✔ ✔ ✔ ✔ ✔
student t ✔ ✔ ✔ ✔ ✔ ✔
triangular ✔ ✔ ✔ ✔ ✔ ✔

Discrete

category distribution PMF statistic fitting random generation note
discrete bernoulli ✔ ✔ ✔ ✔
binary ✔ ✔ - ✔
binomial ✔ ✔ ✔ ✔
categorical ✔ ✔ - ✔
discrete uniform ✔ ✔ ✔ ✔
gausskuzmin ✔ ✔ - ✔
geometric ✔ ✔ ✔ ✔
hyper geometric ✔ ✔ - ✔
logarithmic ✔ ✔ ✔ ✔
negative binomial ✔ ✔ ✔ ✔
poisson ✔ ✔ ✔ ✔
skellam ✔ ✔ ✔ ✔
yule simon ✔ ✔ ✔ ✔
zipf ✔ ✔ ✔ ✔

Usage

NormalDistribution dist = new(mu: 1, sigma: 3);

// PDF
for (ddouble x = -4; x <= 4; x += 0.125) {
    ddouble pdf = dist.PDF(x);

    Console.WriteLine($"pdf({x})={pdf}");
}

// CDF
for (ddouble x = -4; x <= 4; x += 0.125) {
    ddouble ccdf = dist.CDF(x, Interval.Upper);

    Console.WriteLine($"ccdf({x})={ccdf}");
}

// Quantile
for (int i = 0; i <= 10; i++) {
    ddouble p = (ddouble)i / 10;
    ddouble x = dist.Quantile(p, Interval.Upper);

    Console.WriteLine($"cquantile({p})={x}");
}

// Statistic
Console.WriteLine($"Support={dist.Support}");
Console.WriteLine($"Mu={dist.Mu}");
Console.WriteLine($"Sigma={dist.Sigma}");
Console.WriteLine($"Mean={dist.Mean}");
Console.WriteLine($"Median={dist.Median}");
Console.WriteLine($"Mode={dist.Mode}");
Console.WriteLine($"Variance={dist.Variance}");
Console.WriteLine($"Skewness={dist.Skewness}");
Console.WriteLine($"Kurtosis={dist.Kurtosis}");
Console.WriteLine($"Entropy={dist.Entropy}");

// Random Sampling
Random random = new(1234);
double[] xs = dist.Sample(random, 100000).ToArray();

// Fitting
// note: The distribution that minimizes the squared error 
//       of the quantile function over the specified interval is return.
(NormalDistribution? dist_fit, ddouble error) = 
    NormalDistribution.Fit(xs, fitting_quantile_range: (0.1, 0.9));

Typical parameter symbols

category symbol note
support parameter k
a, b uniform
a, b, c triangular
shape parameter alpha
alpha, beta beta, beta prime
gamma, delta johnson sb, su
eta gompertz
nu chi, chisq, student t
n irwin hall
n, m fisher z, snedecor f
c stable distributions
location parameter mu
scale parameter sigma error-related distributions
theta time-related distributions
s, r otherwise
non-centricity parameter lambda
mu non-central student t

To Be Updated

Not Implemented Distributions

(N/A)

Not Implemented Functions

  • Statistic Test

Licence

MIT

Author

T.Yoshimura

Product Compatible and additional computed target framework versions.
.NET net8.0 is compatible.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed.  net9.0 was computed.  net9.0-android was computed.  net9.0-browser was computed.  net9.0-ios was computed.  net9.0-maccatalyst was computed.  net9.0-macos was computed.  net9.0-tvos was computed.  net9.0-windows was computed.  net10.0 was computed.  net10.0-android was computed.  net10.0-browser was computed.  net10.0-ios was computed.  net10.0-maccatalyst was computed.  net10.0-macos was computed.  net10.0-tvos was computed.  net10.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last Updated
1.8.0 182 11/13/2024
1.7.0 155 10/31/2024
1.6.5 210 8/22/2024
1.6.4 150 8/14/2024
1.6.3 152 7/25/2024
1.6.2 190 7/12/2024
1.6.1 118 7/10/2024
1.6.0 167 7/9/2024
1.5.9 178 7/9/2024 1.5.9 is deprecated because it has critical bugs.
1.5.8 141 6/7/2024
1.5.7 162 5/22/2024
1.5.6 168 5/21/2024
1.5.5 150 5/21/2024
1.5.4 155 5/21/2024
1.5.3 164 5/20/2024
1.5.2 156 5/20/2024
1.5.1 178 5/18/2024
1.5.0 188 5/16/2024
1.4.1 167 5/15/2024
1.4.0 147 5/14/2024
1.3.2 159 5/10/2024
1.3.1 172 5/9/2024
1.3.0 160 5/9/2024
1.2.0 172 5/5/2024
1.1.1 176 5/4/2024
1.1.0 161 5/3/2024
1.0.9 146 5/3/2024
1.0.8 143 5/3/2024
1.0.7 161 5/1/2024
1.0.6 185 4/30/2024
1.0.5 156 4/29/2024
1.0.4 162 4/27/2024
1.0.3 177 4/26/2024
1.0.2 185 4/25/2024
1.0.1 182 4/24/2024
1.0.0 161 4/24/2024

feat: fitting discrete