Discrete-Valued Time Series

The analysis and modeling of time series has been an active research area for more than 100 years, with the main focus on time series having a continuous range consisting of real numbers or real vectors. It took until the 1980s for the first papers on discrete-valued time series to appear. In the 20...

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Bibliographische Detailangaben
Format:	Online
Sprache:	Englisch
Veröffentlicht:	MDPI - Multidisciplinary Digital Publishing Institute 2024
Schlagworte:	Granger causality conditional mutual information mixed embedding symbol sequences discrete-valued time series financial complex network autoregressive model count time series INAR bootstrap partial autocorrelation function Yule–Walker equations CMPB thinning operator bounded time series CMPBAR model under-dispersion equi-dispersion over-dispersion INARCH model saddlepoint approximation thinning-based model time series of counts discrete-time Markov chain TP2 transition probability matrix Kalmykov order statistical process control run length Bayesian estimation censored time series convolution closed infinitely divisible Poisson INAR(1) model risk model stochastic premiums INAR(1) process INMA(1) process ruin probability integer-valued time series thinning operator observation-driven ergodicity interval estimation INGARCH conditional distribution dynamic structure robust estimation n onlinear state space model iterated extended Kalman filter Bayesian filtering singular value decomposition n/a thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics
Online-Zugang:	ONIX_20240514_9783725804771_305
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Discrete-Valued Time Series

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