Series to Display (Temporal Causal Modeling)
These options specify the series (targets or inputs) for which output is displayed. The content of the output for the specified series is determined by the Output Options settings.
- Display targets associated with best-fitting models
- By default, output is displayed for the targets that are associated with the 10
best-fitting models, as determined by the R square value. You can specify a different
fixed number of best-fitting models or you can specify a percentage of best-fitting
models. You can also choose from the following goodness of fit measures:
- R square
- Goodness-of-fit measure of a linear model, sometimes called the coefficient of determination. It is the proportion of variation in the target variable explained by the model. It ranges in value from 0 to 1. Small values indicate that the model does not fit the data well.
- Root mean square percentage error
- A measure of how much the model-predicted values differ from the observed values of the series. It is independent of the units that are used and can therefore be used to compare series with different units.
- Root mean square error
- The square root of mean square error. A measure of how much a dependent series varies from its model-predicted level, expressed in the same units as the dependent series.
- BIC
- Bayesian Information Criterion. A measure for selecting and comparing models based on the -2 reduced log likelihood. Smaller values indicate better models. The BIC also "penalizes" overparameterized models (complex models with a large number of inputs, for example), but more strictly than the AIC.
- AIC
- Akaike Information Criterion. A measure for selecting and comparing models based on the -2 reduced log likelihood. Smaller values indicate better models. The AIC "penalizes" overparameterized models (complex models with a large number of inputs, for example).
- Specify Individual Series
-
You can specify individual series for which you want output.
- For column-based data, you specify the fields that contain the series that you want. The order of the specified fields defines the order in which they appear in the output.
- For multidimensional data, you specify a particular series by adding an entry to
the grid for the metric field that contains the series. You then specify the
values of the dimension fields that define the series.
- You can enter the value for each dimension field directly into the grid or you can select from the list of available dimension values. To select from the list of available dimension values, click the ellipsis button in the cell for the dimension that you want. This action opens the Select Dimension Value subdialog.
- You can search the list of dimension values, on the Select Dimension Value subdialog, by clicking the binoculars icon and specifying a search term. Spaces are treated as part of the search term. Asterisks (*) in the search term do not indicate wildcard characters.
- The order of the series in the grid defines the order in which they appear in the output.
For both column-based data and multidimensional data, output is limited to 30 series. This limit includes individual series (inputs or targets) that you specify and targets that are associated with best-fitting models. Individually specified series take precedence over targets that are associated with best-fitting models.