Time Series Analysis Time Series Analysis
    • 124,99 €

Description de l’éditeur

A modern and accessible guide to the analysis of introductory time series data

Featuring an organized and self-contained guide, Time Series Analysis provides a broad introduction to the most fundamental methodologies and techniques of time series analysis. The book focuses on the treatment of univariate time series by illustrating a number of well-known models such as ARMA and ARIMA.

Providing contemporary coverage, the book features several useful and newlydeveloped techniques such as weak and strong dependence, Bayesian methods, non-Gaussian data, local stationarity, missing values and outliers, and threshold models. Time Series Analysis includes practical applications of time series methods throughout, as well as:
Real-world examples and exercise sets that allow readers to practice the presented methods and techniques Numerous detailed analyses of computational aspects related to the implementation of methodologies including algorithm efficiency, arithmetic complexity, and process time End-of-chapter proposed problems and bibliographical notes to deepen readers’ knowledge of the presented material Appendices that contain details on fundamental concepts and select solutions of the problems implemented throughout A companion website with additional data fi les and computer codes
Time Series Analysis is an excellent textbook for undergraduate and beginning graduate-level courses in time series as well as a supplement for students in advanced statistics, mathematics, economics, finance, engineering, and physics. The book is also a useful reference for researchers and practitioners in time series analysis, econometrics, and finance.

Wilfredo Palma, PhD, is Professor of Statistics in the Department of Statistics at Pontificia Universidad Católica de Chile. He has published several refereed articles and has received over a dozen academic honors and awards. His research interests include time series analysis, prediction theory, state space systems, linear models, and econometrics. He is the author of Long-Memory Time Series: Theory and Methods, also published by Wiley.

GENRE
Science et nature
SORTIE
2016
28 avril
LANGUE
EN
Anglais
LONGUEUR
616
Pages
ÉDITIONS
Wiley
DÉTAILS DU FOURNISSEUR
John Wiley & Sons Ltd
TAILLE
18,4
Mo
Bayesian Analysis of Time Series Bayesian Analysis of Time Series
2019
Bayesian Statistics from Methods to Models and Applications Bayesian Statistics from Methods to Models and Applications
2015
Time Series Analysis for the State-Space Model with R/Stan Time Series Analysis for the State-Space Model with R/Stan
2021
Topics in Nonparametric Statistics Topics in Nonparametric Statistics
2014
Topics in Statistical Simulation Topics in Statistical Simulation
2014
Time Series for Data Science Time Series for Data Science
2022
Robust Statistics Robust Statistics
2011
Advanced Statistics with Applications in R Advanced Statistics with Applications in R
2019
Fundamental Statistical Inference Fundamental Statistical Inference
2018
Machine Learning Machine Learning
2018
Applied Longitudinal Analysis Applied Longitudinal Analysis
2012
Understanding Uncertainty Understanding Uncertainty
2013