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Statistics
A Journal of Theoretical and Applied Statistics
Volume 45, 2011 - Issue 1: Statistics on Dependent Data
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Original Articles

Some recent progress in count time series

Pages 49-58 | Received 26 Jun 2010, Published online: 06 Feb 2011

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Haixiang Zhang & Dehui Wang. (2015) Inference for Random Coefficient INAR(1) Process Based on Frequency Domain Analysis. Communications in Statistics - Simulation and Computation 44:4, pages 1078-1100.
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Šárka Hudecová, Marie Hušková & Simos G. Meintanis. (2015) Tests for time series of counts based on the probability-generating function. Statistics 49:2, pages 316-337.
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Articles from other publishers (45)

Malte Jahn & Christian H. Weiß. (2023) Nonlinear GARCH-type models for ordinal time series. Stochastic Environmental Research and Risk Assessment 38:2, pages 637-649.
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Zhongzhen Wang, Petros Dellaportas & Ioannis Kosmidis. (2023) Bayesian tensor factorisations for time series of counts. Machine Learning.
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Sumen Sen, Ishapathik Das & Fathima Ayoob. (2023) Doubly-Inflated Poisson INGARCH Models for Count Time Series. Journal of Statistical Theory and Practice 17:4.
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Juan C. Reboredo, Jose Ramon Barba-Queiruga, Javier Ojea-Ferreiro & Francisco Reyes-Santias. (2023) Forecasting emergency department arrivals using INGARCH models. Health Economics Review 13:1.
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Matthias Kirchner & Giovanni Luca Torrisi. (2023) Fluctuations and precise deviations of cumulative INAR time series. Stochastic Processes and their Applications 164, pages 1-32.
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Malte Jahn, Christian H Weiß & Hee-Young Kim. (2023) Approximately linear INGARCH models for spatio-temporal counts. Journal of the Royal Statistical Society Series C: Applied Statistics 72:2, pages 476-497.
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Luiza S. C. Piancastelli, Wagner Barreto‐Souza & Hernando Ombao. (2022) Flexible bivariate INGARCH process with a broad range of contemporaneous correlation. Journal of Time Series Analysis 44:2, pages 206-222.
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Kee Wah Fo, Seng Huat Ong, Choung Min Ng & You Beng Koh. (2023) An alternative hyper-Poisson integer-valued GARCH model with application to polio, internet protocol and COVID-19 data. AIMS Mathematics 8:12, pages 29116-29139.
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Christian H. Weiß & Malte Jahn. (2022) Soft-clipping INGARCH models for time series of bounded counts. Statistical Modelling, pages 1471082X2211212.
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Peter Congdon. (2022) A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates. Journal of Geographical Systems 24:4, pages 583-610.
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Wagner Barreto‐Souza & Hernando Ombao. (2021) The negative binomial process: A tractable model with composite likelihood‐based inference. Scandinavian Journal of Statistics 49:2, pages 568-592.
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Peter Congdon. (2022) A Model for Highly Fluctuating Spatio-Temporal Infection Data, with Applications to the COVID Epidemic. International Journal of Environmental Research and Public Health 19:11, pages 6669.
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Santosha Rathod, Sridhar Yerram, Prawin Arya, Gururaj Katti, Jhansi Rani, Ayyagari Phani Padmakumari, Nethi Somasekhar, Chintalapati Padmavathi, Gabrijel Ondrasek, Srinivasan Amudan, Seetalam Malathi, Nalla Mallikarjuna Rao, Kolandhaivelu Karthikeyan, Nemichand Mandawi, Pitchiahpillai Muthuraman & Raman Meenakshi Sundaram. (2021) Climate-Based Modeling and Prediction of Rice Gall Midge Populations Using Count Time Series and Machine Learning Approaches. Agronomy 12:1, pages 22.
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Sangyeol Lee & Byungsoo Kim. (2021) Recent progress in parameter change test for integer-valued time series models. Journal of the Korean Statistical Society 50:3, pages 730-755.
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Ana Martins, Manuel Scotto, Ricardo Deus, Alexandra Monteiro & Sónia Gouveia. (2021) Association between respiratory hospital admissions and air quality in Portugal: A count time series approach. PLOS ONE 16:7, pages e0253455.
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Yuan Tian, Dehui Wang & Xinyang Wang. (2021) Order shrinkage and selection for the INGARCH(p,q) model. International Journal of Biomathematics 14:05, pages 2150070.
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Xinyang Wang, Dehui Wang & Kai Yang. (2020) Integer-valued time series model order shrinkage and selection via penalized quasi-likelihood approach. Metrika 84:5, pages 713-750.
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Alessio Farcomeni, Antonello Maruotti, Fabio Divino, Giovanna Jona‐Lasinio & Gianfranco Lovison. (2020) An ensemble approach to short‐term forecast of COVID‐19 intensive care occupancy in Italian regions. Biometrical Journal 63:3, pages 503-513.
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Rodrigo B. Silva & Wagner Barreto‐Souza. (2019) Flexible and Robust Mixed Poisson INGARCH Models. Journal of Time Series Analysis 40:5, pages 788-814.
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Eviyana Atmanegara, Suhartono & RM Atok. (2019) Forecasting Foreign Tourist Using Intervention Analysis On Count Time Series. IOP Conference Series: Materials Science and Engineering 546:5, pages 052014.
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S. Ejaz Ahmed, Khalifa Es-Sebaiy, Abdulkadir Hussein, Idir Ouassou & Anne Snowdon. 2019. Matrices, Statistics and Big Data. Matrices, Statistics and Big Data 177 190 .
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Naif Alzahrani, Peter Neal, Simon E.F. Spencer, Trevelyan J. McKinley & Panayiota Touloupou. (2018) Model selection for time series of count data. Computational Statistics & Data Analysis 122, pages 33-44.
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Jiwon Kang. (2018) Detection of Parameter Change in Random Coefficient Integer-Valued Autoregressive Models. Entropy 20:2, pages 107.
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Jiyoung Lee & Eunju Hwang. (2018) A generalized regime-switching integer-valued GARCH(1, 1) model and its volatility forecasting. Communications for Statistical Applications and Methods 25:1, pages 29-42.
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Christian Weiß. 2018. An Introduction to Discrete‐Valued Time Series. An Introduction to Discrete‐Valued Time Series 257 274 .
Toshifumi Fujiyama, Chihiro Matsui & Akimichi Takemura. (2016) A Power-Law Growth and Decay Model with Autocorrelation for Posting Data to Social Networking Services. PLOS ONE 11:8, pages e0160592.
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Yan Liu, Dehui Wang, Haixiang Zhang & Ningzhong Shi. (2016) Bivariate zero truncated Poisson INAR(1) process. Journal of the Korean Statistical Society 45:2, pages 260-275.
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Carsten Jentsch & Anne Leucht. (2015) Bootstrapping sample quantiles of discrete data. Annals of the Institute of Statistical Mathematics 68:3, pages 491-539.
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J.E. Yoon & S.Y. Hwang. (2015) Zero-Inflated INGARCH Using Conditional Poisson and Negative Binomial: Data Application. Korean Journal of Applied Statistics 28:3, pages 583-592.
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Cong Li, Dehui Wang & Haixiang Zhang. (2015) First-order mixed integer-valued autoregressive processes with zero-inflated generalized power series innovations. Journal of the Korean Statistical Society 44:2, pages 232-246.
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Wagner Barreto-Souza & Marcelo Bourguignon. (2014) A skew INAR(1) process on $${\mathbb {Z}}$$ Z. AStA Advances in Statistical Analysis 99:2, pages 189-208.
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Roland Fried, Inoncent Agueusop, Björn Bornkamp, Konstantinos Fokianos, Jana Fruth & Katja Ickstadt. (2013) Retrospective Bayesian outlier detection in INGARCH series. Statistics and Computing 25:2, pages 365-374.
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J.E. Yoon & S.Y. Hwang. (2015) Integer-Valued GARCH Models for Count Time Series: Case Study. Korean Journal of Applied Statistics 28:1, pages 115-122.
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Ming Yang, Joseph E Cavanaugh & Gideon KD Zamba. (2014) State-space models for count time series with excess zeros. Statistical Modelling 15:1, pages 70-90.
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Hanan Elsaied & Roland Fried. (2014) ROBUST FITTING OF INARCH MODELS. Journal of Time Series Analysis 35:6, pages 517-535.
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Peter Congdon. 2014. Applied Bayesian Modelling. Applied Bayesian Modelling 215 272 .
Célestin C. Kokonendji. 2014. Methods and Applications of Statistics in Clinical Trials. Methods and Applications of Statistics in Clinical Trials 506 526 .
Kamil Feridun Turkman, Manuel González Scotto & Patrícia de Zea BermudezKamil Feridun Turkman, Manuel González Scotto & Patrícia de Zea Bermudez. 2014. Non-Linear Time Series. Non-Linear Time Series 199 244 .
Kamil Feridun Turkman, Manuel González Scotto & Patrícia de Zea BermudezKamil Feridun Turkman, Manuel González Scotto & Patrícia de Zea Bermudez. 2014. Non-Linear Time Series. Non-Linear Time Series 23 89 .
Xanthi Pedeli & Dimitris Karlis. (2013) Some properties of multivariate INAR(1) processes. Computational Statistics & Data Analysis 67, pages 213-225.
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Fukang Zhu. (2012) Modeling time series of counts with COM-Poisson INGARCH models. Mathematical and Computer Modelling 56:9-10, pages 191-203.
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Fukang Zhu. (2012) Modeling overdispersed or underdispersed count data with generalized Poisson integer-valued GARCH models. Journal of Mathematical Analysis and Applications 389:1, pages 58-71.
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Fukang Zhu. (2012) Zero-inflated Poisson and negative binomial integer-valued GARCH models. Journal of Statistical Planning and Inference 142:4, pages 826-839.
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Aleksandar S. Nastić, Miroslav M. Ristić & Hassan S. Bakouch. (2012) A combined geometric INAR(p) model based on negative binomial thinning. Mathematical and Computer Modelling 55:5-6, pages 1665-1672.
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