SAS/ETS 9.22 User''''s Guide 298 ppt

Figure 47.31 Open Existing Model The model window always contains the following controls and fields: Details: tab displays details for the selection highlighted in the left pane... Fit M

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Model Summary of Residual Errors Window

This window displays the residual error analysis for each model equation To open this window, right-click an existing fitted model in the SAS libraries panel and select Residual Errors

Figure 47.29 Model Summary of Residual Errors Window

Actual v/s Predicted Plot Window

This window displays the actual data set and the predicted data set for viewing and analyzing the model prediction power in graphical plots To open this window, right-click an existing fitted model

in the SAS libraries panel and select Actual v/s Predicted Plot

Figure 47.30 Actual v/s Predicted Plot Window

Edit Existing Fitted Model

Open Existing Model

In the SAS/ETS Model Editor window, click the Sources tab In the Display Preference list box, select All Models to display all of the predefined models If necessary, expand items in the Name box Right-click the model name and select Open The model window opens The title of the window corresponds to the structure where the model is located The model window contains a pane

on the left with values such as Variables, Equations, Constraints, and Fit The contents of the right pane change depending on the selection made in the left pane

Figure 47.31 Open Existing Model

The model window always contains the following controls and fields:

Details: tab

displays details for the selection highlighted in the left pane

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SAS Code

provides the SAS statements for this window

Check Syntax

displays any error in the MODEL procedure syntax

OK

runs the model and saves the results

Cancel

closes the window without implementing any changes

Fit Model—Equations

To select which equations to fit, select Equations under Fit in the left pane of the model window In the right pane, select an entry from the Equations Available to Fit: list and click the right-arrow button The equation is moved to Equations to Fit: list

Figure 47.32 Define Equations

This right pane has the following controls and fields:

Equation Available to Fit: list

lists equations that are available to be fit If the list of equations is blank, all model equations that contain parameters are fitted

Equations To Fit: list

displays the equations selected to be fit To delete an equation, select an existing equation and then click the Delete Row button

Fit Model—Input

To specify input data, select Input under Fit in the left pane of the model window The right pane then displays fields where you can select the library name and data set name, map program symbols

to data set variables, and define covariance matrix of equation errors

Figure 47.33 Input Data Set

This right pane has the following controls and fields:

Library Name:

is the name of the library where the current model is located

Data Set Name:

is the name of the input data set against which you want the model fitted

Browse:

opens the data set selection window for selecting an input data set

ID:

specifies a single variable to identify observations in error messages or in other listings and in the output data set The ID variables are usually SAS date or datetime variables You can type any valid SAS variable name in this field or select from the list

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Frequency:

is the time interval (data frequency) for the input data set

Specify

specifies which frequency in the list is to be used in the time series model When you click Specify, the Specify Frequency window opens See the section “Specify Frequency Window”

on page 2938 for more information

Sort By:

indicates how the fit options are sorted This field has two list boxes In the left list box, select the variable by which to sort In the right list box, select Ascending, Descending, or Not Sorted

Weight:

specifies a variable to supply a weighting value to use for each observation in estimating parameters

Missing Value Behavior:

specifies whether missing values are tracked on an equation-by-equation basis or the entire observation is omitted from the analysis when any equation has a missing predicted or actual value for the equation

Program Symbols: table

lists the name, type, and label of the variables in the existing model The type of the variables include endogenous, exogenous, and variable

Data Set: table

lists the name and label of the variables in the data set You can identify the type of each variable by mapping program symbols to data set variables

New Mapping button

creates a new mapping between a model variable selected in the Program Symbols table and

a data set variable selected in the Data Set table This button becomes available only when

a model variable and a data set variable are selected To create a mapping, click , then click an entry in the Program Symbols: table and drag the pointer to an entry in the Data Set: table

Delete button

deletes the selected mapping

Evaluate button

evaluates data

Automatic Mapping button

automatically maps program variables to data set parameters by using their names Click this button to map variables between the Program Symbols and Data Set tables by their variable names If the Program Symbols table contains a variable whose name matches a variable in the Data Set table, these variables are automatically mapped to each other

Covariance Matrix of Equation Errors

specifies the name of the input data set and the name of the library where it is stroed

Fit Model—Method

To specify how the model parameters are to be estimated, select Method under Fit in the left pane

of the model window For more information about available methods of parameters estimation, see Chapter 18, “The MODEL Procedure,” (SAS/ETS User’s Guide)

Figure 47.34 Model Fit Method

This right pane has the following controls and fields:

Estimation Methods check boxes

enable you to select the corresponding estimation method The check boxes correspond to the methods implemented in PROC MODEL, all of which aim to minimize an objective function Divisor of Variance

specifies a degrees-of-freedom correction in estimating the variance matrix This could be the sum of the weights or the sum of the weights minus the model degrees of freedom

Fit Model—Iteration

To specify the parameters for minimizing the objective function, select Iteration under Fit in the left pane of the model window

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Figure 47.35 Model Estimation Iteration

This right pane has the following controls and fields:

Method: options

specifies the Gauss method or Marquardt method Gauss is the default

For the Gauss method, the Gauss-Newton parameter-change vector for a system is computed at the end of each iteration The objective function is then computed at the changed parameter values at the start of the next iteration For the Marquardt method, at each iteration, the objective function is evaluated at the parameters changed by the Marquardt-Levenberg parameter-change vector For more information about available methods of parameter estimation, see Chapter 18,

“The MODEL Procedure” (SAS/ETS User’s Guide)

Maximum Iterations:

specifies the maximum number of Newton iterations performed at each observation and each replication of Monte Carlo simulations

Maximum number of step halvings:

specifies the maximum number of subiterations allowed for an iteration For the Gauss method, this value limits the number of step halvings For the Marquardt method, this value limits the number of times step parameter  can be increased The default is MAXSUBITER=30 See Chapter 18, “The MODEL Procedure” (SAS/ETS User’s Guide), for more information

Minimization Tuning

specifies the Convergence Criteria and Singularity Criteria

Fit Model—Tests

The SAS/ETS Model Editor enables you to perform tests of nonlinear hypotheses on the model parameters

To define statistical tests that are associated with the model parameters, select Tests under Fit in the left pane of the model window Any previously defined parameter tests for the model are listed

Figure 47.36 Fit Tests

This right pane has the following controls and fields:

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Tests

lists tests of nonlinear hypotheses to be performed on the model parameters Test expressions can be composed of parameter names, arithmetic operators, functions, and constants To add a test, click the Add button and enter the parameters for the test To delete a test, select the test and then click the Delete button

Fit Model—Results

To specify which results you want and to save them to an output data set, select Results under Fit in the left pane of the model window The right pane then provides fields where you can specify which results you want to save and where you can specify the library and data set name where the output is saved

Figure 47.37 Output Selection

This right pane has the following controls and fields:

Output

specifies the results from your model fitting that are to be displayed Select the check box for each analysis you want to include in the output data set or select All to display all analyses for each model equation

Estimated Covariance of the Equation Errors

specifies that the cross-equation covariance are to be displayed and also saved in the output data set specified in Data Set Name: in the folder specified in Library Name: In addition, the determinant of the matrices is displayed

Parameter Estimates

specifies that the parameter estimates are to be displayed and also saved in the output data set specified in Data Set Name: in the folder specified in Library Name: Select Include Covariance Matrix of Estimates to also display and save the estimated covariance and correlations matrix

Library Name:

is the name of the library where the model fit results are to be saved

Data Set Name:

is the data set in which you want the model fit results to be saved

Browse:

opens the data set selection window for selecting an output data set

Define the Model Parameters and Variables

To select input variables for use by the SAS/ETS Model Editor and add them to the Variable and Parameter Definitions list, select Parameters and Variables in the left pane of the model window

Figure 47.38 Create New Model Template—Equations