» Thu Jul 11, 2013 5:07 am For univariate statistics, the mode, median, mean and standard deviation are represented, as well as a generic "moment" function which you can use to calculate skewness and curtosis. You may also perform correlations and bivariate regression.
I'd love to add the Chi-Squared statistic, but I can't figure out a way to crosstabulate. Do I need a multi-dimensional array (with while loops etc)?
Spoiler
Scriptname Statistics extends MathFloat[] Function Values(Float[] afArray) Global Float[] ValueList Int Case = afArray.Length Int Code = 0 Float CurrentValue = http://forums.bethsoft.com/topic/1466007-resource-descriptive-statistics-in-papyrus/0.0 While Case> 0 Case -= 1 CurrentValue = http://forums.bethsoft.com/topic/1466007-resource-descriptive-statistics-in-papyrus/afArray[Case] If ValueList.Find(CurrentValue) < 0 ValueList[Code] = CurrentValue Code += 1 EndIf EndWhile Return ValueListEndFunctionFloat[] Function Sort(Float[] afArray) Global Float[] Sorted Float[] ValueList = Values(afArray) Float HighestValue = MaxValue(ValueList) Int Code = 0 While Code < ValueList.Length If ValueList[Code] != HighestValue Sorted[Code] = MinValue(ValueList) ValueList[ValueList.Find(Sorted[Code])] = HighestValue EndIf Code += 1 EndWhile Sorted[Code] = HighestValue Return SortedEndFunctionFloat Function Min(Float af1, Float af2) Global If af1> af2 Return af2 Else Return af1 EndIfEndFunctionFloat Function Max(Float af1, Float af2) Global If Min(af1, af2) == af2 Return af1 Else Return af2 EndIfEndFunctionFloat Function MinValue(Float[] afArray) Global Int Case = afArray.Length - 1 Float LowestValue = http://forums.bethsoft.com/topic/1466007-resource-descriptive-statistics-in-papyrus/afArray[afArray.Length] While Case> 0 Case -= 1 If LowestValue > afArray[Case] LowestValue = afArray[Case] EndIf EndWhile Return LowestValueEndFunctionFloat Function MaxValue(Float[] afArray) Global Int Case = afArray.Length - 1 Float HighestValue = http://forums.bethsoft.com/topic/1466007-resource-descriptive-statistics-in-papyrus/afArray[afArray.Length] While Case> 0 Case -= 1 If HighestValue < afArray[Case] HighestValue = http://forums.bethsoft.com/topic/1466007-resource-descriptive-statistics-in-papyrus/afArray[Case] EndIf EndWhile Return HighestValueEndFunctionInt Function Frequency(Float[] afArray, Float afValue) Global Int Case = afArray.RFind(afValue, afArray.Length - 1) Int Freq = 0 While Case> 0 Case = afArray.RFind(afValue, Case - 1) Freq += 1 EndWhile Return FreqEndFunctionInt[] Function Frequencies(Float[] afArray) Global Int[] Freqs Float[] ValueList = Values(afArray) Int Code = ValueList.Length While Code > 0 Code -= 1 Freqs[Code] = Frequency(afArray, ValueList[Code]) EndWhile Return FreqsEndFunctionFloat Function Sum(Float[] afArray) Global int Case = afArray.Length float Sum While Case > 0 Case -= 1 Sum += afArray[Case] EndWhile Return SumEndFunctionFloat Function Mode(Float[] afArray) Global Int[] Freqs = Frequencies(afArray) Float[] FreqsFloat Int Code = Freqs.Length While Code > 0 Code -= 1 FreqsFloat[Code] = Freqs[Code] as Float EndWhile Int ModalCat = MaxValue(FreqsFloat) as Int Return afArray[ModalCat]EndFunctionFloat Function Median(Float[] afArray) Global Float[] Sorted = Sort(afArray) Float MedCat = Sorted.Length / 2 If MedCat == Math.Floor(MedCat) Return Sorted[MedCat as Int] Else Return (Sorted[Math.Floor(MedCat)] + Sorted[Math.Ceiling(MedCat)]) / 2 EndIfEndFunctionFloat Function Mean(Float[] afArray) Global Return (Sum(afArray) / afArray.Length)EndFunctionFloat Function Variance(Float[] afArray) Global Float Mean = Mean(afArray) Float SumOfSquares = 0.0 Int Case = afArray.Length While Case > 0 Case -= 1 SumOfSquares += Math.Pow((afArray[Case] - Mean), 2) EndWhile Return SumOfSquares / afArray.LengthEndFunctionFloat Function StandardDeviation(Float[] afArray) Global Return Math.sqrt(Variance(afArray))EndFunctionFloat Function Moment(Float[] afArray, Float afCenter, Float k) Global Float SumOfSquares = 0.0 Int Case = afArray.Length While Case > 0 Case -= 1 SumOfSquares += Math.Pow((afArray[Case] - afCenter), k) EndWhileEndFunctionFloat Function Covariance(Float[] afArray1, Float[] afArray2) Global Float Cov Float MeanX = Mean(afArray1) Float MeanY = Mean(afArray2) Float Sum = 0 Int N = Min(afArray1.Length, afArray2.Length) as Int Int Case = N While Case > 0 Case -= 1 Sum += ((afArray1[Case] - MeanX) * (afArray2[Case] - MeanY)) EndWhile Return Sum / NEndFunctionFloat Function Correlation(Float[] afArray1, Float[] afArray2) Global Return Covariance(afArray1, afArray2) / (StandardDeviation(afArray1) * StandardDeviation(afArray2))EndFunctionFloat Function RSquared(Float[] afArray1, Float[] afArray2) Global Return Math.Pow(Correlation(afArray1, afArray2), 2)EndFunctionFloat Function OLSBeta(Float[] afX, Float[] afY) Global Int N = Min(afX.Length, afY.Length) as Int Return (Covariance(afX, afY) * N) / (Variance(afX) * afX.Length)EndFunctionFloat Function OLSConstant(Float[] afX, Float[] afY) Global Return Mean(afY) - (Mean(afX) * OLSBeta(afX, afY))EndFunctionFunction Regression(Float[] afX, Float[] afY) Global Debug.Messagebox(afY + " = " + OLSConstant(afX, afY) + " + " + OLSBeta(afX, afY) + "\nR = " + Correlation(afX, afY) + "\tR2 = " + RSquared(afX, afY))EndFunction
