Time Series Modelling

The analysis and modeling of time series is of the utmost importance in various fields of application. This Special Issue is a collection of articles on a wide range of topics, covering stochastic models for time series as well as methods for their analysis, univariate and multivariate time series,...

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Detalles Bibliográficos
Otros Autores:	Weiss, Christian H. (Editor)
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Materias:	Humanities time series anomaly detection unsupervised learning kernel density estimation missing data multivariate time series nonstationary spectral matrix local field potential electric power forecasting accuracy machine learning extended binomial distribution INAR thinning operator time series of counts unemployment rate SARIMA SETAR Holt–Winters ETS neural network autoregression Romania integer-valued time series bivariate Poisson INGARCH model outliers robust estimation minimum density power divergence estimator CUSUM control chart INAR-type time series statistical process monitoring random survival rate zero-inflation cointegration subspace algorithms VARMA models seasonality finance volatility fluctuation Student’s t-process entropy based particle filter relative entropy count data time series analysis Julia programming language ordinal patterns long-range dependence multivariate data analysis limit theorems integer-valued moving average model counting series dispersion test Bell distribution count time series estimation overdispersion multivariate count data INGACRCH state-space model bank failures transactions periodic autoregression integer-valued threshold models parameter estimation models
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009654671506719

Descripción
Sumario:	The analysis and modeling of time series is of the utmost importance in various fields of application. This Special Issue is a collection of articles on a wide range of topics, covering stochastic models for time series as well as methods for their analysis, univariate and multivariate time series, real-valued and discrete-valued time series, applications of time series methods to forecasting and statistical process control, and software implementations of methods and models for time series. The proposed approaches and concepts are thoroughly discussed and illustrated with several real-world data examples.
Descripción Física:	1 electronic resource (372 p.)

Time Series Modelling

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