SAS® Studio 3.8: Task Reference Guide : SAS Help Center

About This Book

Part 1Data Tasks

List Table Attributes

Characterize Data

Describe Missing Data

Part 2Graph Tasks

Part 3Map Tasks

Part 4Statistics Tasks

Data Exploration

Summary Statistics

Distribution Analysis

Part 5Linear Models

Nonparametric One-Way ANOVA

N-Way ANOVA

Analysis of Covariance

Linear Regression

Binary Logistic Regression

Predictive Regression Models

Generalized Linear Models

Mixed Models

Partial Least Squares Regression

Part 6High-Performance Statistics Tasks

Bin Continuous Data

High-Performance Correlation Analysis

High-Performance Generalized Linear Models

Replace Missing Values

Random Sampling

Part 7Survival Analysis

Nonparametric Survival Analysis

Proportional Hazards Regression

Part 8Multivariate Analysis

Principal Component Analysis

Factor Analysis

Canonical Correlation

Discriminant Analysis

Correspondence Analysis

Multidimensional Preference Analysis

Part 9Cluster Analysis

Compute Similarities and Distances

Cluster Variables

K-Means Clustering

Cluster Observations

Estimate Within-Cluster Covariances

Part 10Power and Sample Size

Part 11Statistical Process Control

Part 12Combinatorics and Probability Tasks

Permutations

Combinations

Same Birthday Probability

Dice Roll Simulation

Coin Toss Simulation

Poker Hand Probability

Part 13Econometrics Tasks

Causal Models

Cross-sectional Data Models

Panel Data Models

Severity Models

Spatial Regression Models

Univariate Time Series Analysis

Multivariate Time Series Analysis

Part 14Forecasting Tasks

Time Series Data Preparation

Time Series Exploration

Modeling and Forecasting

Part 15Network Optimization

Biconnected Components

Minimum Spanning Tree

Minimum Cost Network Flow

Shortest Paths

Transitive Closure

Traveling Salesman Problem

Part 16SAS Viya Prepare and Explore

SAS Viya: Summary

SAS Viya: Transform Data

SAS Viya: Variable Selection

SAS Viya: Sampling

SAS Viya: Partitioning

SAS Viya: Binning

SAS Viya: Imputation

Part 17SAS Viya Unsupervised Learning

SAS Viya: Clustering

SAS Viya: Principal Component Analysis

SAS Viya: Moving Window Principal Component Analysis

SAS Viya: Support Vector Data Description

SAS Viya: Robust Principal Component Analysis

Part 18SAS Viya Supervised Learning

SAS Viya: Linear Regression

SAS Viya: Logistic Regression

SAS Viya: Generalized Linear Models

SAS Viya: Partial Least Squares Regression

SAS Viya: Quantile Regression

SAS Viya: Decision Tree

SAS Viya: Neural Network

SAS Viya: Forest

SAS Viya: Gradient Boosting

SAS Viya: Factorization Machine

SAS Viya: Support Vector Machine

SAS Viya: Bayesian Network

Part 19SAS Viya Evaluate and Implement

SAS Viya: Assess

SAS Viya: Scoring

SAS Viya: Register

Part 20SAS Viya Text Analytics

SAS Viya: Text Summarization

SAS Viya: Text Parsing and Topic Discovery

SAS Viya: Boolean Rules

SAS Viya: Segmentation

SAS Viya: Text Scoring

Part 21SAS Viya Network Analysis and Optimization

SAS Viya: Biconnected Components

SAS Viya: Centrality Metrics

SAS Viya: Summary Statistics

SAS Viya: Community Detection

SAS Viya: Connected Components

SAS Viya: Core Decomposition

SAS Viya: Cycle Detection

SAS Viya: Linear Assignment

SAS Viya: Maximal Cliques

SAS Viya: Minimum Cut

SAS Viya: Minimum Spanning Tree

SAS Viya: Minimum Cost Network Flow

SAS Viya: Reach Network

SAS Viya: Shortest Paths

SAS Viya: Transitive Closure

SAS Viya: Traveling Salesman Problem

Part 22SAS Viya Econometrics

SAS Viya: Cross-sectional Data Models

SAS Viya: Panel Data Models

SAS Viya: Severity Models

SAS Viya: Aggregate Loss Models

SAS Viya: Spatial Regression Models

SAS Viya: Hidden Markov Models

Part 23SAS Viya Forecasting

SAS Viya: Time Series Data Preparation

SAS Viya: Time Series Exploration

SAS Viya: Modeling and Forecasting

Part 24Appendixes

SAS Studio Tasks and Associated Procedures and Licenses

Input Data Sets for Task Examples

References