SAS/IML(R) 9.2 User's Guide
What's New in SAS/IML- New Features
- Modules for Multivariate Random Sampling
- Performance Improvements
- ODS Statistical Graphics Interface
- BSPLINE Function
- Vector-Matrix Operations
- GEOMEAN and HARMEAN Functions
- New Related Software
- Introduction to SAS/IML Software
- Understanding the Interactive Matrix Language
- Defining a Matrix
- Matrix Names and Literals
- Creating Matrices from Matrix Literals
- Scalar Literals
- Numeric Literals
- Character Literals
- Repetition Factors
- Reassigning Values
- Assignment Statements
- Types of Statements
- Missing Values
- Summary
- Tutorial: A Module for Linear Regression
- Working with Matrices
- Overview
- Entering Data as Matrix Literals
- Using Assignment Statements
- Using Matrix Expressions
- Displaying Matrices with Row and Column Headings
- More about Missing Values
- Programming Statements
- Overview
- IF-THEN/ELSE Statements
- DO Groups
- Iterative Execution
- Jumping
- Module Definition and Execution
- Defining and Executing a Module
- Nesting Modules
- Understanding Symbol Tables
- Modules with No Arguments
- Modules with Arguments
- More about Argument Passing
- Module Storage
- Stopping Execution
- Summary
- Working with SAS Data Sets
- Overview
- Opening a SAS Data Set
- Making a SAS Data Set Current
- Displaying SAS Data Set Information
- Referring to a SAS Data Set
- Listing Observations
- Reading Observations from a SAS Data Set
- Using the READ Statement with the VAR Clause
- Using the READ Statement with the VAR and INTO Clauses
- Using the READ Statement with the WHERE Clause
- Editing a SAS Data Set
- Creating a SAS Data Set from a Matrix
- Understanding the End-of-File Condition
- Producing Summary Statistics
- Sorting a SAS Data Set
- Indexing a SAS Data Set
- Data Set Maintenance Functions
- Summary of Commands
- Comparison with the SAS DATA Step
- Summary
- File Access
- Overview
- Referring to an External File
- Reading from an External File
- Writing to an External File
- Listing Your External Files
- Closing an External File
- Summary
- General Statistics Examples
- Overview
- General Statistics Examples
- Example 8.1: Correlation
- Example 8.2: Newton's Method for Solving Nonlinear Systems of Equations
- Example 8.3: Regression
- Example 8.4: Alpha Factor Analysis
- Example 8.5: Categorical Linear Models
- Example 8.6: Regression of Subsets of Variables
- Example 8.7: Response Surface Methodology
- Example 8.8: Logistic and Probit Regression for Binary Response Models
- Example 8.9: Linear Programming
- Example 8.10: Quadratic Programming
- Example 8.11: Regression Quantiles
- Example 8.12: Simulations of a Univariate ARMA Process
- Example 8.13: Parameter Estimation for a Regression Model with ARMA Errors
- Example 8.14: Iterative Proportional Fitting
- Example 8.15: Full-Screen Nonlinear Regression
- References
- Robust Regression Examples
- Overview
- Using LMS and LTS
- Example 9.1: LMS and LTS with Substantial Leverage Points: Hertzsprung-Russell Star Data
- Example 9.2: Comparison of LMS, V7 LTS, and FAST-LTS
- Example 9.3: LMS and LTS Univariate (Location) Problem: Barnett and Lewis Data
- Using MVE and MCD
- Combining Robust Residual and Robust Distance
- References
- Time Series Analysis and Examples
- Overview
- Basic Time Series Subroutines
- Time Series Analysis and Control Subroutines
- Getting Started
- Syntax
- Details
- Minimum AIC Procedure
- Smoothness Priors Modeling
- Bayesian Seasonal Adjustment
- Nonstationary Time Series
- Multivariate Time Series Analysis
- Spectral Analysis
- Computational Details
- Missing Values
- ISM TIMSAC Packages
- Example 10.1: VAR Estimation and Variance Decomposition
- Kalman Filter Subroutines
- Getting Started
- Syntax
- Example 10.2: Kalman Filtering: Likelihood Function Evaluation
- Example 10.3: Kalman Filtering: SSM Estimation With the EM Algorithm
- Example 10.4: Diffuse Kalman Filtering
- Vector Time Series Analysis Subroutines
- Fractionally Integrated Time Series Analysis
- References
- Nonlinear Optimization Examples
- Overview
- Getting Started
- Details
- Global versus Local Optima
- Kuhn-Tucker Conditions
- Definition of Return Codes
- Objective Function and Derivatives
- Finite-Difference Approximations of Derivatives
- Parameter Constraints
- Options Vector
- Termination Criteria
- Control Parameters Vector
- Printing the Optimization History
- Nonlinear Optimization Examples
- Example 11.1: Chemical Equilibrium
- Example 11.2: Network Flow and Delay
- Example 11.3: Compartmental Analysis
- Example 11.4: MLEs for Two-Parameter Weibull Distribution
- Example 11.5: Profile-Likelihood-Based Confidence Intervals
- Example 11.6: Survival Curve for Interval Censored Data
- Example 11.7: A Two-Equation Maximum Likelihood Problem
- Example 11.8: Time-Optimal Heat Conduction
- References
- Graphics Examples
- Overview
- An Introductory Graph
- Details
- Graphics Segments
- Segment Attributes
- Coordinate Systems
- Windows and Viewports
- Clipping Your Graphs
- Common Arguments
- Graphics Examples
- Window and Display Features
- Overview
- Creating a Display Window for Data Entry
- Using the WINDOW Statement
- Using the DISPLAY Statement
- Details about Windows
- Storage Features
- Using SAS/IML Software to Generate IML Statements
- Overview
- Generating and Executing Statements
- Executing a String Immediately
- Feeding an Interactive Program
- Calling the Operating System
- Calling the SAS Windowing Environment
- Executing Any Command in an EXECUTE Call
- Making Operands More Flexible
- Interrupt Control
- Specific Error Control
- General Error Control
- Macro Interface
- IML Line Pushing Contrasted with Using the Macro Facility
- Example 15.1: Full-Screen Editing
- Summary
- Wavelet Analysis
- Overview
- Getting Started
- Creating the Wavelet Decomposition
- Wavelet Coefficient Plots
- Multiresolution Approximation Plots
- Multiresolution Decomposition Plots
- Wavelet Scalograms
- Reconstructing the Signal from the Wavelet Decomposition
- Details
- References
- Genetic Algorithms
- Overview
- Formulating a Genetic Algorithm Optimization
- Choosing the Problem Encoding
- Setting the Objective Function
- Controlling the Selection Process
- Using Crossover and Mutation Operators
- Executing a Genetic Algorithm
- Setting Up the IML Program
- Incorporating Local Optimization
- Handling Constraints
- Example 17.1: Genetic Algorithm with Local Optimization
- Example 17.2: Real-Valued Objective Optimization with Constant Bounds
- Example 17.3: Integer Programming Knapsack Problem
- Example 17.4: Optimization with Linear Constraints Using Repair Strategy
- References
- Sparse Matrix Algorithms
- Overview
- Iterative Methods
- Input Data Description
- Example: Conjugate Gradient Algorithm
- Example: Minimum Residual Algorithm
- Example: Biconjugate Gradient Algorithm
- Symbolic LDL and Cholesky Factorizations
- References
- Further Notes
- Memory and Workspace
- Accuracy
- Error Diagnostics
- Efficiency
- Missing Values
- Principles of Operation
- Operation-Level Execution
- Language Reference
- Overview
- Operators
- Addition Operator: +
- Comparison Operators: < > = <= >= ^=
- Concatenation Operator, Horizontal: ||
- Concatenation Operator, Vertical: //
- Direct Product Operator: @
- Division Operator: /
- Element Maximum Operator: <>
- Element Minimum Operator: ><
- Index Creation Operator: :
- Logical Operators: & | ^
- Multiplication Operator, Elementwise: #
- Multiplication Operator, Matrix: *
- Power Operator, Elementwise: ##
- Power Operator, Matrix: **
- Sign Reverse Operator: -
- Subscripts: [ ]
- Subtraction Operator: -
- Transpose Operator: `
- Statements, Functions, and Subroutines
- ABORT Statement
- ABS Function
- ALL Function
- ANY Function
- APPCORT Call
- APPEND Statement
- APPLY Function
- ARMACOV Call
- ARMALIK Call
- ARMASIM Function
- BLOCK Function
- BRANKS Function
- BSPLINE Function
- BTRAN Function
- BYTE Function
- CALL Statement
- CHANGE Call
- CHAR Function
- CHOOSE Function
- CLOSE Statement
- CLOSEFILE Statement
- COMPORT Call
- CONCAT Function
- CONTENTS Function
- CONVEXIT Function
- COVLAG Function
- CREATE Statement
- CSHAPE Function
- CUSUM Function
- CVEXHULL Function
- DATASETS Function
- DELETE Call
- DELETE Statement
- DESIGN Function
- DESIGNF Function
- DET Function
- DIAG Function
- DISPLAY Statement
- DO Function
- DO and END Statements
- DO Statement, Iterative
- DO DATA Statement
- DO Statement with an UNTIL Clause
- DO Statement with a WHILE Clause
- DURATION Function
- ECHELON Function
- EDIT Statement
- EIGEN Call
- EIGVAL Function
- EIGVEC Function
- END Statement
- EXECUTE Call
- EXP Function
- FARMACOV Call
- FARMAFIT Call
- FARMALIK Call
- FARMASIM Call
- FDIF Call
- FFT Function
- FILE Statement
- FIND Statement
- FINISH Statement
- FORCE Statement
- FORWARD Function
- FREE Statement
- GAEND Call - Experimental
- GAGETMEM Call - Experimental
- GAGETVAL Call - Experimental
- GAINIT Call - Experimental
- GAREEVAL Call - Experimental
- GAREGEN Call - Experimental
- GASETCRO Call - Experimental
- GASETMUT Call - Experimental
- GASETOBJ Call - Experimental
- GASETSEL Call - Experimental
- GASETUP Function - Experimental
- GBLKVP Call
- GBLKVPD Call
- GCLOSE Call
- GDELETE Call
- GDRAW Call
- GDRAWL Call
- GENEIG Call
- GEOMEAN Function
- GGRID Call
- GINCLUDE Call
- GINV Function
- GOPEN Call
- GOTO Statement
- GPIE Call
- GPIEXY Call
- GPOINT Call
- GPOLY Call
- GPORT Call
- GPORTPOP Call
- GPORTSTK Call
- GSCALE Call
- GSCRIPT Call
- GSET Call
- GSHOW Call
- GSORTH Call
- GSTART Call
- GSTOP Call
- GSTRLEN Call
- GTEXT and GVTEXT Calls
- GWINDOW Call
- GXAXIS and GYAXIS Calls
- HADAMARD Function
- HALF Function
- HANKEL Function
- HARMEAN Function
- HDIR Function
- HERMITE Function
- HOMOGEN Function
- I Function
- IF-THEN/ELSE Statement
- IFFT Function
- INDEX Statement
- INFILE Statement
- INPUT Statement
- INSERT Function
- INT Function
- INV Function
- INVUPDT Function
- IPF Call
- ITSOLVER Call
- J Function
- JROOT Function
- KALCVF Call
- KALCVS Call
- KALDFF Call
- KALDFS Call
- LAV Call
- LCP Call
- LENGTH Function
- LINK and RETURN Statements
- LIST Statement
- LMS Call
- LOAD Statement
- LOC Function
- LOG Function
- LP Call
- LTS Call
- LUPDT Call
- MAD Function
- MARG Call
- MATTRIB Statement
- MAX Function
- MAXQFORM Call
- MCD Call
- MIN Function
- MOD Function
- MODULEI Call
- MODULEIC Function
- MODULEIN Function
- MVE Call
- NAME Function
- NCOL Function
- NLENG Function
- Nonlinear Optimization and Related Subroutines
- NLPCG Call
- NLPDD Call
- NLPFDD Call
- NLPFEA Call
- NLPHQN Call
- NLPLM Call
- NLPNMS Call
- NLPNRA Call
- NLPNRR Call
- NLPQN Call
- NLPQUA Call
- NLPTR Call
- NORMAL Function
- NROW Function
- NUM Function
- ODE Call
- ODSGRAPH Call
- OPSCAL Function
- ORPOL Function
- ORTVEC Call
- PAUSE Statement
- PGRAF Call
- POLYROOT Function
- PRINT Statement
- PRODUCT Function
- PURGE Statement
- PUSH Call
- PUT Statement
- PV Function
- QR Call
- QUAD Call
- QUEUE Call
- QUIT Statement
- RANDGEN Call
- RANDSEED Call
- RANK Function
- RANKTIE Function
- RATES Function
- RATIO Function
- RDODT and RUPDT Calls
- READ Statement
- REMOVE Function
- REMOVE Statement
- RENAME Call
- REPEAT Function
- REPLACE Statement
- RESET Statement
- RESUME Statement
- RETURN Statement
- ROOT Function
- ROWCAT Function
- ROWCATC Function
- RUN Statement
- RUPDT Call
- RZLIND Call
- SAVE Statement
- SEQ, SEQSCALE, and SEQSHIFT Calls
- SEQSCALE Call
- SEQSHIFT Call
- SETDIF Function
- SETIN Statement
- SETOUT Statement
- SHAPE Function
- SHOW Statement
- SOLVE Function
- SOLVELIN Call
- SORT Call
- SORT Statement
- SORTNDX Call
- SOUND Call
- SPLINE and SPLINEC Calls
- SPLINEV Function
- SPOT Function
- SQRSYM Function
- SQRT Function
- SSQ Function
- START and FINISH Statements
- STOP Statement
- STORAGE Function
- STORE Statement
- SUBSTR Function
- SUM Function
- SUMMARY Statement
- SVD Call
- SWEEP Function
- SYMSQR Function
- T Function
- TEIGEN Call
- TEIGVAL Function
- TEIGVEC Function
- TOEPLITZ Function
- TPSPLINE Call
- TPSPLNEV Call
- TRACE Function
- TRISOLV Function
- TSBAYSEA Call
- TSDECOMP Call
- TSMLOCAR Call
- TSMLOMAR Call
- TSMULMAR Call
- TSPEARS Call
- TSPRED Call
- TSROOT Call
- TSTVCAR Call
- TSUNIMAR Call
- TYPE Function
- UNIFORM Function
- UNION Function
- UNIQUE Function
- UNIQUEBY Function
- USE Statement
- VALSET Call
- VALUE Function
- VARMACOV Call
- VARMALIK Call
- VARMASIM Call
- VECDIAG Function
- VNORMAL Call
- VTSROOT Call
- WAVFT Call
- WAVGET Call
- WAVIFT Call
- WAVPRINT Call
- WAVTHRSH Call
- WINDOW Statement
- XMULT Function
- XSECT Function
- YIELD Function
- Base SAS Functions Accessible from SAS/IML
- Bitwise Logical Operation Functions
- Character and Formatting Functions
- Character String Matching Functions and Subroutines
- Date and Time Functions
- Descriptive Statistics Functions and Subroutines
- Double-Byte Character String Functions
- External Files Functions
- File I/O Functions
- Financial Functions
- Macro Functions and Subroutines
- Mathematical Functions and Subroutines
- Probability Functions
- Quantile Functions
- Random Number Functions and Subroutines
- State and Zip Code Functions
- Trigonometric and Hyperbolic Functions
- Truncation Functions
- Web Tools
- References
- Module Library
- Overview
- Contents of IMLMLIB
- IMLMLIB and the STORAGE library
- Accessing the IML Source Code
- Order of Resolution
- Error Diagnostics
- Modules for Multivariate Random Sampling
- Modules Reference
- COLVEC Function
- CORR Function
- EXPMATRIX Function
- GBXWHSKR Call
- GPROBCNT Call
- GXYPLOT Call
- MEDIAN Function
- QUADREG Call
- QUARTILE Function
- RANDDIRICHLET Function
- RANDMULTINOMIAL Function
- RANDMVT Function
- RANDNORMAL Function
- RANDWISHART Function
- REGRESS Call
- ROWVEC Function
- RSUBSTR Function
- STANDARD Function
- TABPRT Call
- References
Index here
| Product | Release |
|---|---|
| SAS/IML | 9.2 |
- Type
- Usage and Reference
- Copyright Date
- March 2008
- Last Updated
- 30Sep2009
| Working with Matrices |
Overview
SAS/IML software provides many ways to create matrices. You can create matrices by doing any of the following:
- entering data yourself as a matrix literal
- using assignment statements
- using matrix-generating functions
- creating submatrices from existing matrices with subscripts
- using SAS data sets (see Chapter 6 for more information)
Once you have defined matrices, you have access to many operators and functions for working on them in matrix expressions. These operators and functions facilitate programming and make referring to submatrices efficient and simple.
Finally, you have several means available for tailoring your displayed output.
Copyright © 2009 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
