SIMULATE <copula-name-list>/options;
The SIMULATE statement simulates data from a specified copula model. The copula name specification can be either the name of a defined copula as specified by name in the DEFINE statement or the name of a fitted copula specified in the NAME= option in the FIT statement copula specification.
specifies how the marginal distributions are computed. If MARGINALS=UNIFORM, then the samples are drawn from the copula distribution and marginal distributions are uniform.
MARGINALS=EMPIRICAL can be used to explicitly specify that the marginal distributions are empirical CDF computed from the DATA= option in the PROC COPULA statement.
If the MARGINALS= option is not specified in the SIMULATE statement, then the marginal distributions used in the simulation depend on whether a preceding FIT statement was used: If there is no FIT statement, the marginal distributions depend on whether the PROC COPULA statement includes a DATA= option. If there is a preceding FIT statement, then the marginal distributions from that fit are used. If there is no FIT statement and there is no DATA= option, then MARGINALS=UNIFORM.
specifies the number of draws to generate for this simulation. The default is 100.
specifies the output data set for the random samples from the simulation. This data set is the SAS data set in the OUTUNIFORM= option transformed by the inverse empirical CDF. This option is useful only when an input data exists and MARGINALS=EMPIRICAL. The data set is not created if this option is not specified.
specifies the output data set for the result of the simulation in uniforms. This option can be used when MARGINALS=UNIFORM or when MARGINALS=EMPIRICAL. If MARGINALS=EMPIRICAL, then this option enables you to obtain the samples simulated from the joint distribution specified by the copula, with all marginal distributions being uniform. The data are not created if this option is not specified.
controls the plots that are produced by the COPULA procedure. By default, the PROC COPULA produces a scatter plot matrix for variables. You can specify any of the following global-plot-options:
specifies the maximum number of variables specified in the VAR statement to be displayed in the matrix plot. The NVAR=ALL option uses all variables that are specified in the VAR statement. By default, NVAR=5.
requests that tail dependence plots (chi-plots) be plotted. If you specify this option with the UNPACK option on, PROC COPULA displays a chi-plot for each applicable pair of distinct variables that are specified in the VAR statement. If you specify this option without the UNPACK option, PROC COPULA displays a scatter plot matrix, the lower triangular section shows regular scatter plots between distinct pairs of variables that are specified in the VAR statement, the upper triangular section shows chi-plots for corresponding pairs of variables.
requests scatter plots for pairs of variables. If you specify this option, PROC COPULA displays a scatter plot for each applicable pair of distinct variables that are specified in the VAR statement.
You can specify the following specific-plot-options:
requests the data type to be plotted. DATATYPE=ORIGINAL presents the data in their original marginal distribution; DATATYPE=UNIFORM shows the transformed data with uniform marginal distribution; and DATATYPE=BOTH plots both the original and uniform data types. If MARGINALS=UNIFORM, then the transformation is omitted and the DATATYPE= option is ignored. If there are no input data, then the simulated data can only have uniform marginal distributions; in this case, the DATATYPE= option is ignored.
requests distributional graphs for the case of two variables. DISTRIBUTION=PDF specifies that the theoretical probability density function is provided with both a contour plot and a surface plot. DISTRIBUTION=CDF requests the graph for the theoretical cumulative distribution function of the copula.
suppresses all plots.
specifies the seed for generating random numbers for the simulation. If the seed is not provided, a random number is used as the seed.