Features
RATS is a powerful program, which can perform a range of econometric and statistical operations. The following is a list of the major procedures in econometrics and time series analysis that can be implemented in RATS. All these methods can be used in order to forecast, as well as to conduct data analysis. In addition, RATS can handle cross-sectional and panel data:
- Linear regression, including stepwise.
- Regressions with heteroscedasticity and serial-correlation correction.
- Non-linear least squares.
- Two-stage least squares, three-stage least squares, and seemingly unrelated regressions.
- Non-linear systems estimation.
- Generalized Method of Moments.
- Maximum likelihood estimation.
- Simultaneous equation systems, large econometric models.
- ARIMA (autoregressive, integrated moving average) and transfer function models.
- Spectral analysis.
- Kalman filter and State Space models.
- Neural networks.
- Regressions with discrete dependent variables, such as logistic regressions.
- ARCH and GARCH models.
- Vector autoregressions.
RATS can read data from a variety of file formats and database sources, including Excel files, text files, Stata files, and most databases that support SQL and ODBC. It can handle virtually any data frequency, including daily, weekly, intra-day, and panel data.
RATS has extensive graphics capabilities. It can generate high-resolution time series graphs, high-resolution X-Y scatter plots, dual-scale graphs, and can export graphs to many formats, including PostScript and Windows Metafile.
Read more about this topic: Regression Analysis Of Time Series
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