The SPATIALREG Procedure

specifies the primary SAS data set that contains dependent variables, and explanatory variables, and so on.

specifies the secondary spatial weights data set, which can be used to construct the spatial weights matrix . Loosely speaking, the entries of , , define the amount of influence that a unit has over a unit . The entries must be nonnegative and have zeros on the diagonal; that is, and , where , with n being the total number of spatial units in the data. Any nonzero diagonal elements are replaced with 0. The spatial weights matrix can be asymmetric; that is, it is not necessary that . For information about missing spatial weights in , see the section NONORMALIZE.

The matrix can take two different forms. First, you can provide a full spatial weights matrix. In this case, the data set that you specify in the WMAT= option has n rows. However, the number of columns can be either or n, depending on whether you need a spatial ID variable to match observations in two data sets that are specified by the DATA= option and WMAT= option. If you need a SPATIALID statement to specify a spatial ID variable for the purpose of matching observations, the data set that you specify in the WMAT= option needs to have n+1 columns. In this case, the spatial ID variable can appear in any column in the data set. Otherwise, the number of columns in the data set that you specify in the WMAT= option should be n.

Second, you can also specify the spatial weights matrix by using a compact form when appropriate. In this form, the number of observations in the data set that you specify in the WMAT= option should match the number of nonzero elements in the spatial weights matrix. Moreover, the number of columns in this data set should be three. The first two columns give the row and column indices for nonzero entries in the spatial weights matrix. The third column in the data set contains the nonzero entries in the spatial weights matrix. If you use the compact form for the spatial weights matrix, you must include a SPATIALID statement to match observations in the two data sets that are specified in the DATA= option and WMAT= option. For more information about the SPATIALID statement, see the section SPATIALID Statement. For more information about the compact representation of the spatial weights matrix, see the section Compact Representation of Spatial Weights Matrix.

suppresses the row standardization of the spatial weights matrix that is specified in the WMAT= option. By default, the spatial weights matrix is row-standardized; that is, the spatial weights matrix has unit row sum. If the NONORMALIZE option is specified, spatial weights are used "as is" except for , which is always treated as 0. This implies that an entry in the matrix cannot be missing for if the NONORMALIZE option is specified. If this option is not specified, missing spatial weights are replaced with zeros.

specifies options that are related to approximating the Jacobian, as described in the section Approximations to the Jacobian. You must specify one or more of the following approx-options:

writes the covariance matrix for the parameter estimates to the OUTEST= data set. This option is valid when you specify the OUTEST= option.

writes the parameter estimates to the specified output data set.

prints the correlation matrix of the parameter estimates. You can also specify this option in the MODEL statement.

prints the covariance matrix of the parameter estimates. You can also specify this option in the MODEL statement.

suppresses all printed output.

specifies the type of covariance matrix for the parameter estimates. You can specify the following types:

By default, COVEST=HESSIAN. The quasi-maximum-likelihood estimates are computed using COVEST=QML. For all models except the linear and SLX models, only COVEST=HESSIAN is supported.

specifies the iterative minimization method to use. You can specify the following values:

By default, METHOD=NEWRAP.