RATS 8.0 Pro For Windows (WinRATS Pro 8.0) Serial Key
type.src combines the value of the underlying time series with the given seasonal pattern to obtain the forecast of the resulting type series. the seasonal pattern is supplied by a specified date within the time series and is not necessarily associated with a fixed calendar year. the companion procedure strfor.src computes the estimated tsf (type series forecast) to the given date and the forecast and asl statistics for the resulting forecast of the type time series. type.src also requires the implementation of mbtsft.src which is a stripped-down version of the strfor.src procedure. mbdemo.zip contains all of the above files.
xnetcen is an extension of the netcent package. it provides a number of utility functions for working with centred networks. the package also provides an example dataset. the companion procedure xnetcen.rat is provided in the sample zipped file mbdemo.zip. xnetcen.prg contains the short procedure documenting the built-in functions. mbdemo.zip contains the sample dataset, a short description of the functions in xnetcen.rat, and the installation files for xnetcen.
xrecon is a simulation package to reproduce the spreadsheet-based logistic regression (lr) models used to predict binary or count dependent variables. it also has an associated example dataset with the functions needed to reproduce the model and generate the plot for model tuning. the package has a companion tutorial that will guide you through its functions using sample datasets. xrecon.prg contains the short procedure documenting the built-in functions. mbdemo.zip contains the example dataset, a short description of the functions in xrecon.prg, and the installation files for xrecon.zip.
is a (partial) example program demonstrating the use of rats to perform generalized estimating equations (gee) regression analysis on the data stored in ‘data/gier/.’ that is, you can write code to perform gee regression and hypothesis testing on the data stored in ‘data/gier/.’ this allows you to use your favorite statistical software to perform all of the analysis, and you can save your results to data/gier/ in the same format used for the original data. for example, you could save the results to data/gier/ ‘in’ a dataframe and then use the save.gier() procedure to save the results in the native rats format. rats only requires a file containing the name of the data frame ‘in’ to be present. gee regression is performed using the data stored in data/gier/ ‘in’ and the result is stored in data/gier/.’
is a (partial) example program demonstrating the use of rats to perform generalized estimating equations (gee) regression analysis on the data stored in ‘data/gier/.’ that is, you can write code to perform gee regression and hypothesis testing on the data stored in ‘data/gier/.
rats version 8.0 is new and exciting. version 8.0 has a much more graphical interface, and does a much better job of letting the user edit the parameter estimates directly.0 also adds bootstrapped standard errors and confidence intervals, and greater flexibility in handling the sample data. it also adds an em-algorithm solution for the full sample, which is much more efficient than the earlier solution. in addition, version 8.0 adds many new graphical features such as confidence bands, error bars, and graphing indicators. it also has a much better error handling system, and all of the new features are now accessible to users with no programming experience. finally, version 8.0 improves the integrity of the calculations in the rats econometric package, in some cases correcting errors and providing more accurate answers. the additional features and improvements in version 8.0 are described below.
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