// <copyright file="ExcelFunctions.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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//
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// Copyright (c) 2009-2013 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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using System;
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using IStation.Numerics.Distributions;
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using IStation.Numerics.Statistics;
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#if !NETSTANDARD1_3
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using System.Runtime;
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#endif
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// ReSharper disable InconsistentNaming
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namespace IStation.Numerics
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{
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/// <summary>
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/// Collection of functions equivalent to those provided by Microsoft Excel
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/// but backed instead by Math.NET Numerics.
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/// We do not recommend to use them except in an intermediate phase when
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/// porting over solutions previously implemented in Excel.
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/// </summary>
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public static class ExcelFunctions
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{
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double NormSDist(double z)
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{
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return Normal.CDF(0d, 1d, z);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double NormSInv(double probability)
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{
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return Normal.InvCDF(0d, 1d, probability);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double NormDist(double x, double mean, double standardDev, bool cumulative)
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{
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return cumulative ? Normal.CDF(mean, standardDev, x) : Normal.PDF(mean, standardDev, x);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double NormInv(double probability, double mean, double standardDev)
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{
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return Normal.InvCDF(mean, standardDev, probability);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double TDist(double x, int degreesFreedom, int tails)
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{
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switch (tails)
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{
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case 1:
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return 1d - StudentT.CDF(0d, 1d, degreesFreedom, x);
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case 2:
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return 1d - StudentT.CDF(0d, 1d, degreesFreedom, x) + StudentT.CDF(0d, 1d, degreesFreedom, -x);
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default:
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throw new ArgumentOutOfRangeException(nameof(tails));
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}
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double TInv(double probability, int degreesFreedom)
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{
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return -StudentT.InvCDF(0d, 1d, degreesFreedom, probability/2);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double FDist(double x, int degreesFreedom1, int degreesFreedom2)
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{
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return 1d - FisherSnedecor.CDF(degreesFreedom1, degreesFreedom2, x);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double FInv(double probability, int degreesFreedom1, int degreesFreedom2)
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{
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return FisherSnedecor.InvCDF(degreesFreedom1, degreesFreedom2, 1d - probability);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double BetaDist(double x, double alpha, double beta)
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{
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return Beta.CDF(alpha, beta, x);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double BetaInv(double probability, double alpha, double beta)
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{
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return Beta.InvCDF(alpha, beta, probability);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double GammaDist(double x, double alpha, double beta, bool cumulative)
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{
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return cumulative ? Gamma.CDF(alpha, 1/beta, x) : Gamma.PDF(alpha, 1/beta, x);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double GammaInv(double probability, double alpha, double beta)
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{
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return Gamma.InvCDF(alpha, 1/beta, probability);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double Quartile(double[] array, int quant)
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{
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switch (quant)
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{
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case 0:
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return ArrayStatistics.Minimum(array);
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case 1:
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return array.QuantileCustom(0.25, QuantileDefinition.Excel);
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case 2:
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return array.QuantileCustom(0.5, QuantileDefinition.Excel);
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case 3:
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return array.QuantileCustom(0.75, QuantileDefinition.Excel);
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case 4:
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return ArrayStatistics.Maximum(array);
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default:
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throw new ArgumentOutOfRangeException(nameof(quant));
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}
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double Percentile(double[] array, double k)
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{
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return array.QuantileCustom(k, QuantileDefinition.Excel);
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}
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[TargetedPatchingOptOut("Performance critical to inline this type of method across NGen image boundaries")]
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public static double PercentRank(double[] array, double x)
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{
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return array.QuantileRank(x, RankDefinition.Min);
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}
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}
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}
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// ReSharper restore InconsistentNaming
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