SAS/STAT High-Performance Examples

Examples from Documentation

Select a procedure PROC HPCANDISC PROC HPFMM PROC HPFGAM (NEW) PROC HPGENSELECT PROC HPLMIXED PROC HPLOGISTIC PROC HPNLMOD PROC HPPLS PROC HPPRINCOMP PROC HPQUANTSELECT PROC HPREG PROC HPSPLIT

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HPCANDISC Procedure

• Getting Started: HPCANDISC Procedure

• Example 5.1: Analyzing Iris Data with PROC HPCANDISC
• Example 5.2: Performing Canonical Discriminant Analysis in Single-Machine and Distributed Modes

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HPFMM Procedure

• Mixture Modeling for Binomial Overdispersion: "Student," Pearson, Beer, and Yeast
• Modeling Zero-Inflation: Is It Better to Fish Poorly or Not to Have Fished at All?
• Looking for Multiple Modes: Are Galaxies Clustered?

• Example 6.1: Modeling Mixing Probabilities: All Mice Are Equal, but Some Mice Are More Equal Than Others
• Example 6.2: The Usefulness of Custom Starting Values: When Do Cows Eat?
• Example 6.3: Enforcing Homogeneity Constraints: Count and Dispersion—It Is All Over!

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HPFGAM Procedure

• Mixture Modeling for Binomial Overdispersion: "Student," Pearson, Beer, and Yeast
• Modeling Zero-Inflation: Is It Better to Fish Poorly or Not to Have Fished at All?
• Looking for Multiple Modes: Are Galaxies Clustered?

• Example 6.1: Modeling Mixing Probabilities: All Mice Are Equal, but Some Mice Are More Equal Than Others
• Example 6.2: The Usefulness of Custom Starting Values: When Do Cows Eat?
• Example 6.3: Enforcing Homogeneity Constraints: Count and Dispersion—It Is All Over!

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HPGENSELECT Procedure

• Getting Started: HPGENSELECT Procedure

• Example 7.1: Model Selection
• Example 7.2: Modeling Binomial Data
• Example 7.3: Tweedie Model
• Example 7.4: Model Selection by the LASSO Method

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HPLMIXED Procedure

• Mixed Model Analysis of Covariance with Many Groups

• Example 8.1: Computing BLUPs for a Large Number of Subjects

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HPLOGISTIC Procedure

• Binary Logistic Regression

• Example 9.1: Model Selection
• Example 9.2: Modeling Binomial Data
• Example 9.3: Ordinal Logistic Regression
• Example 9.4: Partitioning Data

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HPNLMOD Procedure

• Least Squares Model
• Binomial Model

• Example 10.1: Segmented Model

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HPPLS Procedure

• Spectrometric Calibration

• Example 11.1: Choosing a PLS Model by Test Set Validation
• Example 11.2: Fitting a PLS Model in Single-Machine and Distributed Modes

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HPPRINCOMP Procedure

• Getting Started: HPPRINCOMP Procedure

• Example 12.1: Analyzing Mean Temperatures of US Cities
• Example 12.2: Computing Principal Components in Single-Machine and Distributed Modes
• Example 12.3: Extracting Principal Components with NIPALS

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HPQUANTSELECT Procedure

• Getting Started: HPQUANTSELECT Procedure

• Example 13.1: Simulation Study
• Example 13.2: Growth Charts for Body Mass Index

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HPREG Procedure

• Getting Started: HPREG Procedure

• Example 14.1: Model Selection with Validation
• Example 14.2: Backward Selection in Single-Machine and Distributed Modes
• Example 14.3: Forward-Swap Selection
• Example 14.4: Forward Selection with Screening

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HPSPLIT Procedure

• Getting Started: HPSPLIT Procedure

• Example 15.1: Building a Classification Tree for a Binary Outcome
• Example 15.2: Cost-Complexity Pruning with Cross Validation
• Example 15.3: Creating a Regression Tree
• Example 15.4: Creating a Binary Classification Tree with Validation Data
• Example 15.5: Assessing Variable Importance

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