The following options appear on the *T**i*me Series*Partition Data* dialog.

**Time Variable**

From the **Variables** list, select a time variable and click > to move the variable to the **Variables in the Partitioned Data **list. If a time variable is not selected, Analytic Solver assigns one to the partitioned data.

**Variables in the Partitioned Data**

Select one or more variables from the **Variables** list and click > to move them into this list.

**Specify Partitioning Options**

Under Specify Partitioning Options, select Specify percentages to specify the percentage of the total number of records in the Validation Set or Training Set. Select Specify # records to enter the desired number of records in the Validation Set or Training Set.

**Specify percentages and Specify # records**

Select Automatic to have Analytic Solver automatically use 60% of the records in the Training Set and 40% of the records in the Validation Set. Under Specify Partitioning Options, select Specify # records to manually select the number of records to include in the Validation Set or Training Set. If Specify percentages is selected, then specify the percentage of the total number of records to be included in the Validation Set or Training Set.

On the Analytic Solver ribbon, from the **Time Series** tab, select **ARIMA - Autocorrelations** to display the *ACF* dialog.

**Variables In Input Data**

Select one or more variables from the **Selected variable** list and click the < to move them to the **Variables In Input Data** list.

**Selected variable**

From the **Variables in Input Data** list, select a variable to use for the autocorrelations.

**Parameters:Training**

Enter the minimum and maximum lags for the Training Data here. The # lags for the Training set should be >= 1 and < N where N is the number of records in the Training dataset.

**Parameters: Validation**

Enter the minimum and maximum lags for the Validation Data here. The # lags for the Validation Data set should be >= 1 and < N where N is the number of records in the Validation dataset.

**Plot PACF chart**

If this option is selected, Analytic Solver plots the partial autocorrelations for the selected variable.

**Plot ACF chart**

If this option is selected, Analytic Solver plots the autocorrelations for the selected variable.

**Plot ACVF chart**

If this option is selected, Analytic Solver plots the autocovariance of data for the selected variable.

**Time Variable**

The Time variable is automatically selected when using a partitioned dataset. When using an unpartitioned dataset, select the desired Time variable by clicking the > button.

**Selected Variable**

The selected variable appears here.

**Fit seasonal model**

Select this option to specify a seasonal model. The seasonal parameters are enabled when this option is selected.

**Period**

If Fit seasonal model is selected, this option is enabled. Seasonality in a dataset appears as patterns at specific periods in the time series.

**Nonseasonal Parameters**

Enter the nonseasonal parameters here for Autoregressive (p), Difference (d), and Moving Average (q).

**Seasonal Parameters**

Enter the Seasonal parameters here for Autoregressive (P), Difference (D), and Moving Average (Q).

The options below appear on the *ARIMA - Advanced Options* dialog.

**Maximum number of iterations**

Enter the maximum number of iterations here.

**Fitted Values and residuals**

Analytic Solver Data Mining will include the fitted values and residuals in the output if this option is selected.

**Variance-covariance matrix**

Analytic Solver Data Mining will include the variance-covariance matrix in the output if this option is selected.

**Produce forecasts**

If this option is selected, Analytic Solver Data Mining will display the desired number of forecasts. If the data has been partitioned, Analytic Solver will display the forecasts on the validation data.

**Number of forecasts**

If *Produce forecasts* is selected and a non-partitioned dataset is being used, this option is enabled. The maximum number of forecasts is 100.

**Confidence level for forecast confidence intervals**

If this option is selected, enter the desired confidence level here. (The default level is 95%.) The Lower and Upper values of the computed confidence levels will be included in the output. The forecasted value will be guaranteed to fall within this range for the specified confidence level.