Here you find a collection of Free Time Series Analysis Software modules (Calculators). The modules have been grouped in Univariate, Bivariate, and Trivariate categories. All modules can be used with any dataset that contains ungrouped observations.

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Univariate Time Series Analysis & Forecasting - Time Series
(Partial) Autocorrelation Functioncomputes the autocorrelation and partial autocorrelation function for any univariate time series
Variance Reduction Matrixcomputes the Variance Reduction Matrix that can be used to determine which combination of seasonal and non-seasonal differencing.
Standard Deviation-Mean Plotcomputes the Standard Deviation-Mean Plot and the Range Mean Plot
Spectral Analysiscomputes the raw periodogram and the cumulative periodogram of a univariate time series (with the 95% Kolmogorov-Smirnov confidence intervals)
ARIMA Backward Selectioncomputes the ARIMA Backward Selection approach
ARIMA Forecasting computes the forecasts of a univariate ARIMA model.
Classical Decompositioncomputes the Classical Seasonal Decomposition of a univariate time series by Moving Averages
Decomposition by Loesscomputes the Seasonal Decomposition by Loess as proposed by Cleveland et al.
Structural Time Series Modelscomputes the following Structural Time Series Models
Exponential Smoothingcomputes the various exponential smoothing models, and generates forecasts
Bivariate Time Series Analysis & Forecasting - Time Series
Cross Correlation Functioncomputes the Cross Correlation Function for any bivariate time series
Bivariate Granger Causalitycomputes the bivariate Granger causality test in two directions.
Trivariate Time Series Analysis & Forecasting - Time Series
Multivariate Time Series Analysis & Forecasting - Time Series