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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Year of Publication:2021
Language:English
Physical Description:1 electronic resource (372 p.)
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520 |a 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. 
546 |a English 
650 7 |a Humanities  |2 bicssc 
653 |a time series 
653 |a anomaly detection 
653 |a unsupervised learning 
653 |a kernel density estimation 
653 |a missing data 
653 |a multivariate time series 
653 |a nonstationary 
653 |a spectral matrix 
653 |a local field potential 
653 |a electric power 
653 |a forecasting accuracy 
653 |a machine learning 
653 |a extended binomial distribution 
653 |a INAR 
653 |a thinning operator 
653 |a time series of counts 
653 |a unemployment rate 
653 |a SARIMA 
653 |a SETAR 
653 |a Holt–Winters 
653 |a ETS 
653 |a neural network autoregression 
653 |a Romania 
653 |a integer-valued time series 
653 |a bivariate Poisson INGARCH model 
653 |a outliers 
653 |a robust estimation 
653 |a minimum density power divergence estimator 
653 |a CUSUM control chart 
653 |a INAR-type time series 
653 |a statistical process monitoring 
653 |a random survival rate 
653 |a zero-inflation 
653 |a cointegration 
653 |a subspace algorithms 
653 |a VARMA models 
653 |a seasonality 
653 |a finance 
653 |a volatility fluctuation 
653 |a Student’s t-process 
653 |a entropy based particle filter 
653 |a relative entropy 
653 |a count data 
653 |a time series analysis 
653 |a Julia programming language 
653 |a ordinal patterns 
653 |a long-range dependence 
653 |a multivariate data analysis 
653 |a limit theorems 
653 |a integer-valued moving average model 
653 |a counting series 
653 |a dispersion test 
653 |a Bell distribution 
653 |a count time series 
653 |a estimation 
653 |a overdispersion 
653 |a multivariate count data 
653 |a INGACRCH 
653 |a state-space model 
653 |a bank failures 
653 |a transactions 
653 |a periodic autoregression 
653 |a integer-valued threshold models 
653 |a parameter estimation 
653 |a models 
776 |z 3-0365-2121-6 
776 |z 3-0365-2122-4 
700 1 |a Weiss, Christian H.  |4 oth 
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