Modeling count time series: a comparative case study

被引：0

作者：

Maia, Gisele O. ^{[1
]}

Franco, Glaura C. ^{[1
]}

Santos, Thiago R. ^{[1
]}

Camara, Ana Julia A. ^{[2
]}

机构：

[1] Univ Fed Minas Gerais UFMG, Dept Estat, Belo Horizonte, Brazil

[2] Univ Fed Espirito Santo UFES, Dept Estat, Espirito Santo, Brazil

来源：

SIGMAE | 2024年 / 13卷 / 01期

关键词：

Observation-driven model; Parameter-driven model; GAM-ARMA; NGSSEML; count data; DRIVEN; REGRESSION;

D O I：

暂无

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This paper presents an application for counting data, where the observation-driven and parameter -driven models are compared. To this purpose, the Generalized Additive Autoregressive Moving Average (GAM -ARMA) and Non-Gaussian State Space with Exact Marginal Likelihood (NGSSEML) models are used. Model parameters are estimated using the maximum likelihood method. The ability of the procedure to model and forecast real data is presented for the number of chronic obstructive disease (COPD) cases.

引用

下载

页码：13 / 23

页数：11

共 50 条

[21] Zero-modified count time series modeling with an application to influenza cases
Andrade, Marinho G.
Conceicao, Katiane S.
Ravishanker, Nalini
ASTA-ADVANCES IN STATISTICAL ANALYSIS, 2024, 108 (03) : 611 - 637
[22] Introducing Hybrid Modeling with Time-Series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization
Sitapure, Niranjan
Kwon, Joseph Sang-Il
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2023, 62 (49) : 21278 - 21291
[23] Nonparametric forecasting in time series -: A comparative study
Vilar-Fernandez, Juan M.
Cao, Ricardo
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2007, 36 (02) : 311 - 334
[24] Biclustering fMRI time series: a comparative study
Castanho, Eduardo N.
Aidos, Helena
Madeira, Sara C.
BMC BIOINFORMATICS, 2022, 23 (01)
[25] Bayesian comparative study on binary time series
Paul, Erina
Maity, Arnab Kumar
Maiti, Raju
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2018, 88 (14) : 2811 - 2826
[26] A Comparative Study of Visualizations for Multiple Time Series
Franke, Max
Knabben, Moritz
Lang, Julian
Koch, Steffen
Blascheck, Tanja
PROCEEDINGS OF THE 17TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (IVAPP), VOL 3, 2022, : 103 - 112
[27] Biclustering fMRI time series: a comparative study
Eduardo N. Castanho
Helena Aidos
Sara C. Madeira
BMC Bioinformatics, 23
[28] A comparative study of neural network and Box-Jenkins ARIMA modeling in time series prediction
Ho, SL
Xie, M
Goh, TN
COMPUTERS & INDUSTRIAL ENGINEERING, 2002, 42 (2-4) : 371 - 375
[29] Latent Gaussian Count Time Series
Jia, Yisu
Kechagias, Stefanos
Livsey, James
Lund, Robert
Pipiras, Vladas
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2023, 118 (541) : 596 - 606
[30] Stationary count time series models
Weiss, Christian H.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 2021, 13 (01)

← 1 2 3 4 5 →