Applied Partial Differential Equations - A Visual Approach - P. Markowich (Springer, 2007) WW.pdf

Partial Differential Equations第四版

This book introduces one of the most powerful tools of modern economics to a wide audience: those who will later construct or consume game-theoretic models. Robert Gibbons addresses scholars in applied fields within economics who want a serious and thorough discussion of game theory but who may have found other works overly abstract. Gibbons emphasizes the economic applications of the theory at least as much as the pure theory itself; formal arguments about abstract games play a minor role. The applications illustrate the process of model building--of translating an informal description of a multi-person decision situation into a formal game-theoretic problem to be analyzed. Also, the variety of applications shows that similar issues arise in different areas of economics, and that the same game-theoretic tools can be applied in each setting. In order to emphasize the broad potential scope of the theory, conventional applications from industrial organization have been largely replaced by applications from labor, macro, and other applied fields in economics. The book covers four classes of games, and four corresponding notions of equilibrium: static games of complete information and Nash equilibrium, dynamic games of complete information and subgame-perfect Nash equilibrium, static games of incomplete information and Bayesian Nash equilibrium, and dynamic games of incomplete information and perfect Bayesian equilibrium.

应用组合数学 第二版 冯速译 习题答案

Introduction to Random Signals and Applied Kalman Filtering,4版代码，好东西 学习信号处理和卡尔曼滤波经典教材的代码

Robert Grover Brown , Patrick Y. C. Hwang 经典的卡尔曼滤波书籍，清晰第4版。 In this updated edition the main thrust is on applied Kalman filtering. Chapters 1-3 provide a minimal background in random process theory and the response of linear systems to random inputs. The following chapter is devoted to Wiener filtering and the remainder of the text deals with various facets of Kalman filtering with emphasis on applications. Starred problems at the end of each chapter are computer exercises. The authors believe that programming the equations and analyzing the results of specific examples is the best way to obtain the insight that is essential in engineering work.

贝叶斯应用方面教程。 Bayesian analysis of data in the health，social and physical sciences has been greatly facilitated in the last decade by advances in computing power and improved scope for estimation via iterative sampling methods. Yet the Bayesian perspective，which stresses the accumulation ofknowledge about parameters in a synthesis of prior knowledge with the data at hand，has a longer history. Bayesian methods in econometrics，including applications to linear regression，serial correlation in time series，and simultaneous equations，have been developed since the 1960s with the seminal work of Box and Tiao (1973) and Zellner (1971). Early Bayesian applications in physics are exemplified by the work of Jaynes (e.g. Jaynes，1976) and are discussed，along with recent applications， by D?Agostini (1999). Rao (1975) in the context of smoothing exchangeable parameters and Berry (1980) in relation to clinical trials exemplify Bayes reasoning in biostatistics and biometrics， and it is here that many recent advances have occurred.

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This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 . Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.

Applied Control Theory is, first and foremost, not a substitute for years of formal education about control systems. With that out of the way, it's a very solid primer/reference for those of us who aren't control engineers, but have occasional control problems that need analysis. It's pretty light on math and formal proofs; you break it out when you've got a problem and a deadline and need to wrap it up so that you can get to the 15 other things on your open issues list. In part, it's a book length expansion of Wescott's earlier article, PID without a Ph.D, available at [...] . If you like his writing there, you'll like it here. It's a good reference for engineers who know it but need to occasionally brush back up. It's a good learning guide for programmers who don't know engineering but find themselves suddenly expected to do control theory. It is, however, a lousy book for an engineer to lend to one of his programmers; they tend to scarper off with it, and then you don't have your copy anymore.