Time Series Analyzer - program information

Time Series Analyzer is tool for time series analyzing, creating of regression models, smoothing, seasonal adjustment, hypothesis testing, prediction, curves making, etc. Application has very nice visually output for many of supported areas. Minimum starting settings, possibility to implemement that changes later.

What is new ?: Triple Holt-Winters exponential smoothing ! PACF ! Box-Jenkins !

Supported areas:

1. Base: Original data, Mean difference, Variance, Cumulative, ACF.
2. Statistics: Histogram, Cumulative histogram, N_P plot.
3. Differences: First difference, Second difference, Third difference, Growth rate, Relative increment (%).
4. Transformations: Ln(y), Square root(y), Standardization(y), Normalization(y).
5. Partial sums: 2,3,4,5,6 parts.
6. Moving averages smoothing. Simple, centered.
7. Median smoothing.
8. Exponential smoothing: single (first-order), single (Brown`s), double, double (Holt`s).
9. Regressions: Polynomial (Constant, Linear, Quadratic, Cubic, 4th, 5th), Exponential, Modified Exponential, Power, Gompertz, Logistic.
10. Regressions residuals.
11. Autocorrelations: ACF, PACF.
12. Box-Jenkins: AR, MA, ARMA process.
13. Seasonal adjustment: Additive, multiplicative, constant seasonal model.
14. Seasonal smoothing: Triple Holt-Winters exponential smoothing.
15. Additive and multiplicative decomposition.>
16. Curves:B-Spline, Chaikin, Catmull-Rom, Ferguson.


17. Hypothesis Testing:Kolmogorov-Smirnov (KS), Kolmogorov-Smirnov (Lilliefors/Van Soest variant), W/S normality, D`Agostino, Shapiro-Wilk, Jarque-Bera (chi-square), Jarque-Bera (Lagrange multiplier), Jarque-Bera (advanced Lageange multiplier) test.

Scheduled areas for next development:

Spectral analyzes, Arima, Dependency finder, Neural Network modelling etc.

You can download it on Download page. More application screenshots are here.