Applied Nonparametric Regression
by Wolfgang Härdle
Publisher: Cambridge University Press 1992
Number of pages: 433
This book represents an optimally estimated common thread for the numerous topics and results in the fast-growing area of nonparametric regression. The user-friendly approach taken by the author has successfully smoothed out most of the formidable asymptotic elaboration in developing the theory. This is an excellent collection for both beginners and experts.
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by Martin Hairer - arXiv
This text is an attempt to give a reasonably self-contained presentation of the basic theory of stochastic partial differential equations, taking for granted basic measure theory, functional analysis and probability theory, but nothing else.
by Noel Corngold - Caltech
The book introduces students to the ideas and attitudes that underlie the statistical modeling of physical, chemical, biological systems. The text contains material the author have tried to convey to an audience composed mostly of graduate students.
by Klaus Bichteler - University of Texas
Written for graduate students of mathematics, physics, electrical engineering, and finance. The students are expected to know the basics of point set topology up to Tychonoff's theorem, general integration theory, and some functional analysis.
by Albert Tarantola - SIAM
The first part deals with discrete inverse problems with a finite number of parameters, while the second part deals with general inverse problems. The book for scientists and applied mathematicians facing the interpretation of experimental data.