Time Series Processes

Basic ARMA Processes

MAProcess — moving-average process (scalar and vector)

ARProcess — autoregressive process (scalar and vector)

ARMAProcess — autoregressive moving-average process (scalar and vector)

Integrated and Seasonal ARMA Processes

SARIMAProcess — seasonal integrating ARMA for polynomial and periodic trends

ARIMAProcess ▪ SARMAProcess ▪ FARIMAProcess

Process Framework »

RandomFunction — simulate a time series process

EstimatedProcess — estimate parameters in a time series process

TimeSeriesForecast — forecast future values in a time series process

TemporalData — time series data

FindProcessParameters ▪ AdjustTimeSeriesForecast

CovarianceFunction ▪ CorrelationFunction ▪ AbsoluteCorrelationFunction ▪ PartialCorrelationFunction ▪ PowerSpectralDensity

Model Properties and Representations

WeakStationarity — conditions for a time series model to be weakly stationary

TimeSeriesInvertibility — conditions for a time series model to be invertible

ToInvertibleTimeSeries — gives an invertible representation of the time series

Time Series Data Processing »

UnitRootTest — test whether time series data is stationary

Differences — detrending and deseasoning data

MovingAverage — moving-average filtering

• Random Processes
• Probability & Statistics
• Data Transforms and Smoothing
• Signal Processing
• Regression Models