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Modern Statistical Methods for Astronomy: With R Applications
Modern Statistical Methods for Astronomy: With R Applications

Modern astronomical research is beset with a vast range of statistical challenges, ranging from reducing data from megadatasets to characterizing an amazing variety of variable celestial objects or testing astrophysical theory. Linking astronomy to the world of modern statistics, this volume is a unique resource, introducing astronomers to...

Hidden Markov Models for Time Series: An Introduction Using R (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
Hidden Markov Models for Time Series: An Introduction Using R (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

Reveals How HMMs Can Be Used as General-Purpose Time Series Models

Implements all methods in R
Hidden Markov Models for Time Series: An Introduction Using R applies hidden Markov models (HMMs) to a wide range of time series types, from continuous-valued, circular, and
...

MATLAB Optimization Techniques
MATLAB Optimization Techniques

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or...

Introduction to the Mathematical and Statistical Foundations of Econometrics (Themes in Modern Econometrics)
Introduction to the Mathematical and Statistical Foundations of Econometrics (Themes in Modern Econometrics)

This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit...

Translating Statistics to Make Decisions: A Guide for the Non-Statistician
Translating Statistics to Make Decisions: A Guide for the Non-Statistician

Examine and solve the common misconceptions and fallacies that non-statisticians bring to their interpretation of statistical results. Explore the many pitfalls that non-statisticians―and also statisticians who present statistical reports to non-statisticians―must avoid if statistical results are to be correctly used for...

Better Business Decisions from Data: Statistical Analysis for Professional Success
Better Business Decisions from Data: Statistical Analysis for Professional Success

Everyone encounters statistics on a daily basis. They are used in proposals, reports, requests, and advertisements, among others, to support assertions, opinions, and theories. Unless you’re a trained statistician, it can be bewildering. What are the numbers really saying or not saying? Better Business Decisions from Data:...

Positive Trigonometric Polynomials and Signal Processing Applications (Signals and Communication Technology)
Positive Trigonometric Polynomials and Signal Processing Applications (Signals and Communication Technology)
"The book under review is a new contribution on the topic, with a focus on signal processing applications. … this is the first self-contained manuscript on this emerging research area, and hence it is a welcome and timely contribution to the technical literature. … use of illustrative numerical examples, accompanied by Matlab...
Data Analysis Using SAS Enterprise Guide
Data Analysis Using SAS Enterprise Guide

The present book, Data Analysis Using SAS Enterprise Guide, provides readers with an overview of Enterprise Guide, the newest point-and-click interface from SAS. SAS Enterprise Guide is a graphical user (point-and-click) interface to the main SAS application, having relatively recently replaced the Analyst interface, which itself had replaced...

S+Functional Data Analysis User's Guide
S+Functional Data Analysis User's Guide
S+Functional Data Analysis is the first commercial object oriented package for exploring, modeling, and analyzing functional data. Functional data analysis (FDA) handles longitudinal data and treats each observation as a function of time (or other variable). The functions are related. The goal is to analyze a sample of functions instead of a...
Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)
Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)

In the early days of pattern recognition and statistical data analysis life was rather simple: datasets were relatively small, collected from well-designed experiments, analyzed using a few methods that had good theoretical background. Explosive growth of the use of computers led to the creation of huge amounts of data of all kinds,...

Statistical Methods in Analytical Chemistry (Chemical Analysis: A Series of Monographs on Analytical Chemistry and Its Applications)
Statistical Methods in Analytical Chemistry (Chemical Analysis: A Series of Monographs on Analytical Chemistry and Its Applications)

This new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments. Complete with examples from the chemical and pharmaceutical laboratory and manufacturing areas, this thoroughly updated book clearly...

Risk and Portfolio Analysis: Principles and Methods (Springer Series in Operations Research and Financial Engineering)
Risk and Portfolio Analysis: Principles and Methods (Springer Series in Operations Research and Financial Engineering)

Investment and risk management problems are fundamental problems for  financial institutions and involve both speculative and hedging decisions. A structured approach to these problems naturally leads one to the field of applied mathematics in order to translate subjective probability beliefs and attitudes towards risk and reward into...

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