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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| Language: | English |
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MDPI - Multidisciplinary Digital Publishing Institute
2024
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| Online Access: | ONIX_20240514_9783725804771_305 |
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| 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 |