ml_ts_arma_mle library

Classes

Arima

===== ARIMA fit (exact MLE via innovations; multiplicative seasonal via combine) =====

ArimaFit

ArimaOrder

================= Orders / Fits =================

CHResult

LjungBoxResult

============ Ljung–Box otomatik lag + df düzeltmesi ============

NelderMead

Simple Nelder–Mead (parameter search)

OCSBResult

============ OCSB & Canova–Hansen (alternatives for nsdiffs) ============

Sarima

===== SARIMA (multiplicative combine → ARMA) =====

SarimaFit

SarimaOrder

Functions

acf(List<double> x, int maxLag) → List<double>

armaInnovationsFromPhiTheta(List<double> phi, List<double> theta) → _ArmaInnovations

autocov(List<double> x, int maxLag) → List<double>

canovaHansen(List<double> x, int s) → CHResult

combineAR(List<double> phi, List<double> Phi, int s) → List<double>

combineMA(List<double> theta, List<double> Theta, int s) → List<double>

differenceND(List<double> x, int d, int s, int D) → List<double>

differenceOrd(List<double> x, int d) → List<double>

============ Differencing ============

differenceSeas(List<double> x, int s, int D) → List<double>

exactArmaLogLik(List<double> y, List<double> phi, List<double> theta) → _ExactArmaMLE

invertND(List<double> history, List<double> diffs, int d, int s, int D) → List<double>

invertOrd(List<double> base, List<double> diffs, int d) → List<double>

invertSeas(List<double> base, List<double> diffs, int s, int D) → List<double>

levinsonDurbin(List<double> r, int p) → List<double>

ljungBoxAuto(List<double> resid, {int nParams = 0, String rule = 'sqrt'}) → LjungBoxResult

mean(List<double> x) → double

nsdiffsAuto(List<double> x, int s) → int

Automatic nsdiffs selection: evaluate OCSB and CH together

ocsb(List<double> x, int s, {int? kLags}) → OCSBResult

variance(List<double> x) → double