ml_ts_advanced
library
Functions
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acf(List<double> x, int maxLag)
→ List<double>
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adf(List<double> x, {int? maxLags})
→ ADFResult
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armaCssLoss(List<double> y, List<double> ar, List<double> ma, double mu)
→ double
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armaResiduals(List<double> y, List<double> ar, List<double> ma, double mu)
→ List<double>
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Basit ARMA CSS residual & loss
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autocov(List<double> x, int maxLag)
→ List<double>
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chiSquareCDF(double x, int k)
→ double
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chiSquareSF(double x, int k)
→ double
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diagnoseResiduals(List<double> resid, {int maxLag = 20, int nParams = 0, List<double>? ar, List<double>? ma})
→ Diagnostics
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differenceND(List<double> x, int d, int s, int D)
→ List<double>
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Combined (d and D) differencing and inverse
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differenceOrd(List<double> x, int d)
→ List<double>
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Differencing and inverse differencing (d)
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differenceSeas(List<double> x, int s, int D)
→ List<double>
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Seasonal differencing
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invertND(List<double> history, List<double> diffs, int d, int s, int D)
→ List<double>
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invertOrd(List<double> history, List<double> diffs, int d)
→ List<double>
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invertSeas(List<double> history, List<double> diffs, int s, int D)
→ List<double>
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isARStationary(List<double> phi)
→ bool
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isMAInvertible(List<double> theta)
→ bool
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jarqueBera(List<double> resid)
→ JBResult
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kpss(List<double> x, {int? nwLags})
→ KPSSResult
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levinsonDurbin(List<double> r, int p)
→ List<double>
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Levinson–Durbin (Yule–Walker) => AR phi katsayıları
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ljungBox(List<double> resid, int h, {int nParams = 0})
→ LjungBoxResult
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mean(List<double> x)
→ double
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Temel istatistik ve yardımcılar
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ndiffs(List<double> x, {int maxD = 2})
→ int
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nsdiffs(List<double> x, int s, {int maxD = 1})
→ int
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pacf(List<double> x, int maxLag)
→ List<double>
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PACF (Durbin-Levinson’den köşegen): pratik ve hızlı tahmin
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polyRoots(List<double> a)
→ List<Complex>
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variance(List<double> x)
→ double
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