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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Published: MDPI - Multidisciplinary Digital Publishing Institute 2024
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collection Directory of Open Access Books
description 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 2000s, a rapid increase in research activity was noted, but only in the last few years was a certain maturity and consolidation of the area of discrete-valued time series observed. This reprint is a collection of articles on a wide range of topics on discrete-valued time series (especially count time series), covering stochastic models and methods for their analysis, univariate and multivariate time series, applications of time series methods to risk analysis, statistical process control, and many more. The proposed approaches and concepts are thoroughly discussed and illustrated with several real-world data examples.
format Online
id doab-20.500.12854ir-137708
institution Directory of Open Access Books
language eng
publishDate 2024
publishDateRange 2024
publishDateSort 2024
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
record_format ojs
spelling doab-20.500.12854ir-1377082024-05-14T14:12:15Z Discrete-Valued Time Series Weiss, Christian H. 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 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 2000s, a rapid increase in research activity was noted, but only in the last few years was a certain maturity and consolidation of the area of discrete-valued time series observed. This reprint is a collection of articles on a wide range of topics on discrete-valued time series (especially count time series), covering stochastic models and methods for their analysis, univariate and multivariate time series, applications of time series methods to risk analysis, statistical process control, and many more. The proposed approaches and concepts are thoroughly discussed and illustrated with several real-world data examples. 2024-05-14T14:12:03Z 2024-05-14T14:12:03Z 2024 book ONIX_20240514_9783725804771_305 9783725804771 9783725804788 https://directory.doabooks.org/handle/20.500.12854/137708 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/8933 https://mdpi.com/books/pdfview/book/8933 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-0478-8 10.3390/books978-3-7258-0478-8 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725804771 9783725804788 222 open access
spellingShingle 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
Discrete-Valued Time Series
title Discrete-Valued Time Series
title_full Discrete-Valued Time Series
title_fullStr Discrete-Valued Time Series
title_full_unstemmed Discrete-Valued Time Series
title_short Discrete-Valued Time Series
title_sort discrete valued time series
topic 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
topic_facet 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
url ONIX_20240514_9783725804771_305