Providing software solutions since 1976
Capabilities
- Analysis of Variance
- Bayesian Analysis
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- Cluster Analysis
- Descriptive Statistics
- Distribution Analysis
- Discriminant Analysis
- Exact Methods
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- Market Research
- Missing Value Imputation
- Mixed Models
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- Nonparametric Statistics
- Power and Sample Size
- Psychometric Analysis
- Regression
- Spatial Analysis
- Structural Equations
- Survey Sampling and Analysis
- Survival Analysis
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- SAS/STAT Procedures A-Z
The SIM2D Procedure
- produces a spatial simulation for a Gaussian random field with a specified mean and covariance structure in two dimensions by using an LU decomposition technique. The simulation can be conditional or unconditional
- specify the mean structure as a quadratic function in the coordinates
- specify the covariance by naming the form and supplying the associated parameters, or by using the contents of an item store file that was previously created by PROC VARIOGRAM
- specify the locations of simulation points in a GRID statement, or they can be read from a SAS data set
- handles anisotropic and nested semivariogram models
- supports seven covariance models:
- Gaussian
- exponential
- spherical
- cubic
- pentaspherical
- sine hole effect
- Matérn
- supports a single nugget effect
- obtain separate analyses on observations in groups
- writes the simulated values for each grid point to an output data set
- uses ODS to create a SAS data set corresponding to any table
- supports ODS Graphics
For further details see the SAS/STAT User's Guide:
The SIM2D Procedure
( PDF | HTML )
Examples
Statistics and Operations Research Home Page | SAS/STAT Software
