Tuesday, January 13, 2009

SAS System for RegressionThird Edition or Optimal Control Systems

SAS System for Regression,Third Edition

Author: Rudolf Jakob Freund

Learn to perform a wide variety of regression analyses using SAS software with this example-driven revised favorite from SAS Publishing. With this third edition you will learn the basics of performing regression analyses using a wide variety of models including nonlinear models. Other topics include performing linear regression analyses using PROVC REG and diagnosing and providing remedies for data problems, including outliers and multicollinearity. Examples feature numerous SAS procedures including REG, PLOT, GPLOT, NLIN, RSREG, AUTOREG, PRINCOMP, and others. A helpful discussion of theory is supplied where necessary. Some knowledge of both regression and the SAS System are assumed. The updated third edition includes revisions, updated material, and new material. You'll find information on using SAS/INSIGHT software, regression with a binary response with emphasis on PROC LOGISTIC, and nonparametric regression (smoothing) using moving averages and PROC LOESS. Additionally, updated material throughout the book includes high-resolution PROC REG graphics output, data sets by the OUTEST option described and illustrated, and using PROC SCORE to predict another data set. Supports releases 6.12 and higher of SAS software.

Table of Contents:
Chapter 1Regression Concepts1
1.1Statistical Background1
1.2Performing a Regression with the IML Procedure9
1.3Regression with the SAS System12
Chapter 2Using the REG Procedure15
2.2A Model with One Independent Variable17
2.3A Model with Several Independent Variables20
2.4Various MODEL Statement Options24
2.5Further Examination of Model Parameters36
2.6Plotting Results43
2.7Creating Data I: the OUTPUT Statement52
2.8Creating Data II: Other Data Sets55
2.9Creating Data III: ODS Output57
2.10Predicting to a Different Set of Data57
2.11Exact Collinearity: Linear Dependency60
Chapter 3Observations63
3.2Outlier Detection64
3.3Specification Errors77
3.4Heterogeneous Variances81
3.5Correlated Errors86
Chapter 4Multicollinearity: Detection and Remedial Measures95
4.2Detecting Multicollinearity97
4.3Model Restructuring101
4.4Variable Selection108
4.5Biased Estimation120
Chapter 5Curve Fitting127
5.2Polynomial Models with One Independent Variable128
5.3Polynomial Plots132
5.4Polynomial Models with Several Variables134
5.5Response Surface Plots138
5.6A Three-Factor Response Surface Experiment142
5.7Curve Fitting without a Model148
Chapter 6Special Applications of Linear Models157
6.2Multiplicative Models158
6.3Spline Models164
6.4Indicator Variables169
6.5Binary Response Variable: Logistic Regression173
Chapter 7Nonlinear Models185
7.2Estimating the Exponential Decay Model186
7.3Fitting a Growth Curve with the NLIN Procedure192
7.4Fitting Splines with Unknown Knots198
7.5Additional Comments on the NLIN Procedure203
Chapter 8Using SAS/INSIGHT Software for Regression207
8.2Multiple Linear Regression: the BOQ Data207
8.3A Polynomial Response Surface: the FISH Data215
8.4Logistic Regression: the DYSTRO Data218
8.5Nonparametric Smoothing: the Barbados Data221

New interesting textbook: Indoor Grilling or White Wine For Dummies

Optimal Control Systems

Author: D Subbaram Naidu

The theory of optimal control systems has grown and flourished since the 1960's. Many texts, written on varying levels of sophistication, have been published on the subject. Yet even those purportedly designed for beginners in the field are often riddled with complex theorems, and many treatments fail to include topics that are essential to a thorough grounding in the various aspects of and approaches to optimal control.
Optimal Control Systems provides a comprehensive but accessible treatment of the subject with just the right degree of mathematical rigor to be complete but practical. It provides a solid bridge between "traditional" optimization using the calculus of variations and what is called "modern" optimal control. It also treats both continuous-time and discrete-time optimal control systems, giving students a firm grasp on both methods. Among this book's most outstanding features is a summary table that accompanies each topic or problem and includes a statement of the problem with a step-by-step solution. Students will also gain valuable experience in using industry-standard MATLAB and SIMULINK software, including the Control System and Symbolic Math Toolboxes.
Diverse applications across fields from power engineering to medicine make a foundation in optimal control systems an essential part of an engineer's background. This clear, streamlined presentation is ideal for a graduate level course on control systems and as a quick reference for working engineers.


Naidu (Idaho State University) introduces the theory and concepts useful for optimizing the control of physical systems which are dynamic and hence described by ordinary differential equations. Written for a second level graduate course, the textbook covers the calculus of variations, the linear quadratic regulator system, discrete-time systems, the Pontryagin minimum principle, and constraints on control and state variables. MATLAB and SIMULINK implementations are provided. Annotation c. Book News, Inc., Portland, OR

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