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Think Bayes

de Allen B. Downey

If you know how to program with Python and also know a little about probability, you’re ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code...

Handbook of Measure Theory: In two volumes

de E. Pap

The main goal of this Handbook is

to survey measure theory with its many different branches and its

relations with other areas of mathematics. Mostly aggregating many classical branches of measure theory the aim...

Functional Equations in Applied Sciences

de Enrique Castillo, Andres Iglesias & Reyes Ruiz-Cobo

The book provides the reader with the different types of functional equations that s/he can find in practice, showing, step by step, how they can be solved.

A general methodology for solving functional equations...

Sobolev Spaces

de Robert A. Adams & John J. F. Fournier

Sobolev Spaces presents an introduction to the theory of Sobolev Spaces and other related spaces of function, also to the imbedding characteristics of these spaces. This theory is widely used in pure and Applied...

Handbook of Dynamical Systems

de B. Fiedler

This handbook is volume II in a series collecting mathematical state-of-the-art surveys in the field of dynamical systems. Much of this field has developed from

interactions with other areas of science, and...

An Introduction to Probability and Statistical Inference

de George G. Roussas

Roussas introduces readers with no prior knowledge in probability or statistics, to a thinking process to guide them toward the best solution to a posed question or situation. An Introduction to Probability...

Elements of Random Walk and Diffusion Processes

de Oliver C. Ibe

Presents an important and unique introduction to random walk theory

Random walk is a stochastic process that has proven to be a useful model in understanding discrete-state discrete-time processes across a wide...

Functional Inequalities Markov Semigroups and Spectral Theory

de Fengyu Wang

In this book, the functional inequalities are introduced to describe:

(i) the spectrum of the generator: the essential and discrete spectrums, high order eigenvalues, the principle eigenvalue, and the spectral...

Chances Are . . .: Adventures in Probability

de Michael Kaplan

A compelling journey through history, mathematics, and philosophy, charting humanity’s struggle against randomness

Our lives are played out in the arena of chance. However little we recognize it in our day-to-day...

A Mathematician at the Ballpark: Odds and Probabilities for Baseball Fans

de Ken Ross

In A Mathematician at the Ballpark, professor Ken Ross reveals the math behind the stats. This lively and accessible book shows baseball fans how to harness the power of made predictions and better understand...

Convex Functions, Partial Orderings, and Statistical Applications

de Josip E. Peajcariaac & Y. L. Tong

This research-level book presents up-to-date information concerning recent developments in convex functions and partial orderings and some applications in mathematics, statistics, and reliability theory. The...

Statistical Bioinformatics: with R

de Sunil K. Mathur

Designed for a one or two semester senior undergraduate or graduate bioinformatics course, Statistical Bioinformatics takes a broad view of the subject - not just gene expression and sequence analysis, but a...

Markov Chains

de D. Revuz

This is the revised and augmented edition of a now classic book which is an introduction to sub-Markovian kernels on general measurable spaces and their associated homogeneous Markov chains. The first part,...

Student Solutions Manual for Essential Statistics, Regression, and Econometrics

de Gary Smith

Essential Statistics, Regression, and Econometrics provides students with a readable, deep understanding of the key statistical topics they need to understand in an econometrics course. It is innovative in its...

Mathematical Statistics with Applications

de K.M. Ramachandran & Chris P. Tsokos

Mathematical Statistics with Applications provides a calculus-based theoretical introduction to mathematical statistics while emphasizing interdisciplinary applications as well as exposure to modern statistical...

An Introduction to Stochastic Modeling, Student Solutions Manual (e-only)

de Mark Pinsky & Samuel Karlin

An Introduction to Stochastic Modeling, Student Solutions Manual (e-only)

Guidebook to R Graphics Using Microsoft Windows

The Spectral Analysis of Time Series

de Lambert H. Koopmans

To tailor time series models to a particular physical problem and to follow the working of various techniques for processing and analyzing data, one must understand the basic theory of spectral (frequency domain)...

Applied Linear Regression

de Sanford Weisberg

Master linear regression techniques with a new edition of a classic text

Reviews of the Second Edition:

"I found it enjoyable reading and so full of interesting material that even the well-informed reader will...

Linear Models: A Mean Model Approach

de William R. Moser, Zbynek Sidak & David Aldous

Linear models, normally presented in a highly theoretical and mathematical style, are brought down to earth in this comprehensive textbook. Linear Models examines the subject from a mean model perspective, defining...