05234nam 2200697Ia 450 991102034770332120200520144314.09786613294814978128329481212832948189781118150238111815023697811181502451118150244(CKB)2550000000056521(EBL)818791(SSID)ssj0000554342(PQKBManifestationID)11330146(PQKBTitleCode)TC0000554342(PQKBWorkID)10514311(PQKB)10924460(MiAaPQ)EBC818791(OCoLC)761319820(Perlego)2750589(EXLCZ)99255000000005652119920909d1993 uy 0engur|n|---|||||txtccrAlternative methods of regression /David Birkes, Yadolah DodgeNew York John Wiley19931 online resource (248 p.)Wiley Series in Probability and Statistics ;v.190Description based upon print version of record.9780471568810 0471568813 Includes bibliographical references and index.Alternative Methods of Regression; Contents; Preface; Acknowledgments; 1. Linear Regression Analysis; 1.1 Introduction; 1.2 Example; 1.3 The Linear Regression Model; 1.4 Estimating the Regression Coefficients; 1.5 Testing the Significance of the Relationship; 1.6 The Need for Alternative Methods; 1.7 The Origin of the Word ""Regression""; Notes; References; 2. Constructing and Checking the Model; 2.1 Introduction; 2.2 Checking the Model; 2.3 Modifying the Model; 2.4 Examples; Notes; References; 3. Least-Squares Regression; 3.1 Introduction; 3.2 An Example of Simple Regression3.3 Estimating the Regression Line3.4 Testing β = 0; 3.5 Checking Normality; 3.6 An Example of Multiple Regression; 3.7 Estimating the Regression Coefficients; 3.8 Testing the Regression Coefficients; 3.9 Testing βq + 1 = · · · = βp = 0; 3.10 Testing β3 = 0; 3.11 The Coefficient of Determination; 3.12 Computation; Notes; References; 4. Least-Absolute-Deviations Regression; 4.1 Introduction; 4.2 Estimating the Regression Line; 4.3 Nonuniqueness and Degeneracy; 4.4 Testing β = 0; 4.5 An Example of Multiple Regression; 4.6 Estimating the Regression Coefficients4.7 Testing βq + 1 = · · · = βp = 04.8 Computation; Notes; References; 5. M-Regression; 5.1 Introduction; 5.2 An Example of Simple Regression; 5.3 Estimating the Regression Line; 5.4 Testing β = 0; 5.5 An Example of Multiple Regression; 5.6 Estimating the Regression Coefficients; 5.7 Testing βq + 1 = · · · = βp = 0; 5.8 Computation; Notes; References; 6. Nonparametric Regression; 6.1 Introduction; 6.2 An Example of Simple Regression; 6.3 Estimating the Regression Line; 6.4 Testing β = 0; 6.5 An Example of Multiple Regression; 6.6 Estimating the Regression Coefficients6.7 Testing βq + 1 = · · · = βp = 06.8 Computation; Notes; References; 7. Bayesian Regression; 7.1 Introduction; 7.2 The Bayesian Approach; 7.3 An Example of Simple Regression; 7.4 Estimating the Regression Line; 7.5 Testing β = 0; 7.6 An Example of Multiple Regression; 7.7 Estimating the Regression Coefficients; 7.8 Testing βq + 1 = · · · = βp = 0; 7.9 Computation; Notes; References; 8. Ridge Regression; 8.1 Introduction; 8.2 An Example of Simple Regression; 8.3 Estimating the Regression Line; 8.4 An Example of Multiple Regression; 8.5 Standardization8.6 Estimating the Regression Coefficients8.7 Collinearity; Notes; References; 9. Comparisons; 9.1 Introduction; 9.2 Comparison of Properties; 9.3 Comparisons on Three Data Sets; Notes; References; 10. Other Methods; 10.1 Introduction; 10.2 Other Methods of Linear Regression; 10.3 More General Methods of Regression; References; Appendix; Student's t-Distribution; F-Distribution; Chi-squared Distribution; IndexOf related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts "".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models."" --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all dataWiley Series in Probability and StatisticsRegression analysisMultivariate analysisRegression analysis.Multivariate analysis.519.5/36519.536Birkes David103520Dodge Yadolah1944-29867MiAaPQMiAaPQMiAaPQBOOK9911020347703321Alternative methods of regression437966UNINA04027nam 22006375 450 991064588790332120230121112216.0981-19-7291-510.1007/978-981-19-7291-1(MiAaPQ)EBC7184879(Au-PeEL)EBL7184879(CKB)26037407800041(DE-He213)978-981-19-7291-1(PPN)267810024(EXLCZ)992603740780004120230121d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAdvanced Optimal Control and Applications Involving Critic Intelligence /by Ding Wang, Mingming Ha, Mingming Zhao1st ed. 2023.Singapore :Springer Nature Singapore :Imprint: Springer,2023.1 online resource (283 pages)Intelligent Control and Learning Systems,2662-5466 ;6Includes index.Print version: Wang, Ding Advanced Optimal Control and Applications Involving Critic Intelligence Singapore : Springer,c2023 9789811972904 A Survey of Robust Adaptive Critic Control Design -- Robust Optimal Control of Nonlinear Systems with Matched Uncertainties -- Observer-Based Online Adaptive Regulation for a Class of Uncertain Nonlinear Systems -- Adaptive Tracking Control of Nonlinear Systems Subject to Matched Uncertainties -- Event-Triggered Robust Stabilization Incorporating an Adaptive Critic Mechanism -- An Improved Adaptive Optimal Regulation Framework with Robust Control Synthesis -- Robust Stabilization and Trajectory Tracking of General Uncertain Nonlinear Systems -- Event-Triggered Nonlinear H∞ Control Design via an Improved Critic Learning Strategy -- Intelligent Critic Control with Disturbance Attenuation for a Micro-Grid System -- Sliding Mode Design for Load Frequency Control with Power System Applications.This book intends to report new optimal control results with critic intelligence for complex discrete-time systems, which covers the novel control theory, advanced control methods, and typical applications for wastewater treatment systems. Therein, combining with artificial intelligence techniques, such as neural networks and reinforcement learning, the novel intelligent critic control theory as well as a series of advanced optimal regulation and trajectory tracking strategies are established for discrete-time nonlinear systems, followed by application verifications to complex wastewater treatment processes. Consequently, developing such kind of critic intelligence approaches is of great significance for nonlinear optimization and wastewater recycling. The book is likely to be of interest to researchers and practitioners as well as graduate students in automation, computer science, and process industry who wish to learn core principles, methods, algorithms, and applications in the field of intelligent optimal control. It is beneficial to promote the development of intelligent optimal control approaches and the construction of high-level intelligent systems.Intelligent Control and Learning Systems,2662-5466 ;6Automatic controlRoboticsAutomationMachine learningControl, Robotics, AutomationMachine LearningAutomationAutomatic control.Robotics.Automation.Machine learning.Control, Robotics, Automation.Machine Learning.Automation.006.3Wang Ding1071455Zhao MingmingHa Mingming MiAaPQMiAaPQMiAaPQBOOK9910645887903321Advanced Optimal Control and Applications Involving Critic Intelligence3006282UNINA