Improved Parallel Algorithm for Time Series Based Forecasting Using OTIS-Mesh
ARIMA: ARIMA Models for Time Series Data
Most Complete Solution manual for Operations Research: An Introduction - Hamdy A. Taha (8th ed) (ISBN 0131889230) DOWNLOAD NOW
An Introduction to Partial Differential Equations with MATLAB (Chapman & Hall/Crc Applied Mathematics & Nonlinear Science) by Matthew P. Coleman
Modeling sequential context effects in judgment analysis: A time series approach
NEW EVIDENCE ON THE IMPACT OF FINANCIAL LEVERAGE ON BETA RISK: A TIME SERIES APPROACH
An Introduction To Java Web Technology
Understanding Media and Culture: An Introduction to Mass Communication, v. 1.0, Jack Lule, ISBN: 978-1-4533-2918-4, T E S T B A N K
Financial Accounting An Introduction to Concepts Methods and Uses Stickney 13th Edition Solutions Manual
Materials Science and Engineering: An Introduction Callister Rethwisch 8th Edition Solutions Manual
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 multivariate series to binary data, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out computations for parameter estimation, model selection and checking, decoding, and forecasting.
Illustrates the methodology in action
After presenting the simple Poisson HMM, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference. Through examples and applications, the authors describe how to extend and generalize the basic model so it can be applied in a rich variety of situations. They also provide R code for some of the examples, enabling the use of the codes in similar applications.
Effectively interpret data using HMMs
This book illustrates the wonderful flexibility of HMMs as general-purpose models for time series data. It provides a broad understanding of the models and their uses.
Use coupon below to get discount at eCampus.com!
$3 off textbook orders over $75
$4 off textbook orders over $90
$5 off textbook orders over $100
Copy the coupon code before clicking the button!
|Amazon US||Paperback||$77.68 - $86.95|
Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches ...
Since 1975, The Analysis of Time Series: An Introduction has introduced legions of statistics students and researchers to the theory and practice of time series analysis. With ...
A thorough review of the most current regression methods in time series analysis Regression methods have been an integral part of time series analysis for over a century. Recently, new developments ...
This book provides a protocol for conducting gauge repeatability and reproducibility (R&R) experiments. Such an experiment is required whenever a new test system is developed to monitor a ...
Cluster analysis is an unsupervised process that divides a set of objects into homogeneous groups. This book starts with basic information on cluster analysis, including the classification of data ...
The Reuters Financial Training Series An Introduction to Foreign Exchange & Money Markets A new concept in financial education training, An Introduction to Foreign Exchange & Money Market is ...
Models for Ecological Data: An Introduction
The Analysis of Time Series: An Introduction
Hidden Markov Models for Speech Recognition
Hidden Markov Models for Bioinformatics