1 comments about The Theory of Transformation Groups.

1. As the title of my review suggests, this IS where one should start learning about the subject. Other books which could then be tackled (in any order, really) are: Bredon's classic, tom Dieck (especially if you're wondering about the connections with representation theory and stable homotopy), Guillemin et al. on equivariant de Rham theory (with a view toward applications), Allday+Puppe and Hsiang on hard-core cohomological methods, among others. Note that Borel's seminar on transformation groups is a little out of date, but still worth looking into. Much more recently, P. May compiled quite a few very interesting articles addressing the equivariant stable homotopy category, attributing them to R. Piacenza.

   There are many other avenues one can pursue after reading Kawakubo. I've only listed a few. Good luck :o)

No comments about Elements of Mathematics: Chapters 1-5.

2 comments about Simulation (Statistical Modeling and Decision Science).

1. This is an excelent textbook explaining what simulation means and how to deepen your knowalge. You have to be a good programmer in order to use this book (and simulation generally)and the author should have added an andex for such a language and how its connection with simualtion ( C or C++) although my experience would elect MATLAB as prefernce!! This text does not requir any prior experience regarding simulatin although taking a course in statistics and probability would be advantageous!!



2. According to the books I have consulted by S. M. Ross, I consider him to
   be a tremendous author, with this book being my absolute favourite. It
   is inspirational, clear, creative and (most of all) fun to read.
   
   Starting off from the very basics regarding probability, random numbers
   and generation of random variables, Professor Ross steadily guides the
   reader through, for instance, simulation with respect to some queueing
   systems, validation techniques (e.g. goodness-of-fit tests;
   Kolmogorov-Smirnov tests), the standard MCMC-methods and various variance
   reduction techniques. The latter chapter is the one that I found most
   enlightening including, for instance, a certainly rewarding section on
   importance sampling (weighted simulation). Throughout, a lot of
   well-chosen examples enhance students/readers understanding and interest
   of the subject.
   
   One might note that this is by no means the most advanced or complete book
   on Monte Carlo simulation out there, see e.g.
   
   Monte Carlo Statistical Methods (Springer Texts in Statistics)
   
   or
   
   Stochastic Simulation: Algorithms and Analysis (Stochastic Modelling and Applied Probability),
   
   rather it evolves at an intermediate level covering a few more advanced
   concepts as, for example, coupling from the past. But, having this in
   mind, this is the book to get. Pure concentrated fun (xiii+274 pages).
   Final note: In 2006 the fourth edition was launched. [Simulation, Fourth Edition]

No comments about Köthe-Bochner Function Spaces (Progress in Mathematics).

No comments about Introduction to the Analysis of Metric Spaces (Australian Mathematical Society Lecture Series).

No comments about Ideal Spaces (Lecture Notes in Mathematics).

1 comments about Classical Banach Spaces I and II: Sequence Spaces; Function Spaces (Classics in Mathematics).

1. This book is an excellent survey of Banach Space Theory, and an invaluable resource. It's too terse, but then again, most reference books are.

No comments about Locally Conformal Kahler Geometry (Progress in Mathematics).

No comments about Gâteaux Differentiability of Convex Functions and Topology: Weak Asplund Spaces (Wiley-Interscience and Canadian Mathematics Series of Monographs and Texts).

No comments about Invariant Subspaces.