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001-es BibID:	BIBFORM075889
Első szerző:	Ispány Márton (informatikus, matematikus)
Cím:	On Generalized Additive Models with Dependent Time Series Covariates / Márton Ispány, Valdério A. Reisen, Glaura C. Franco, Pascal Bondon, Higor H. A. Cotta, Paulo R. P. Filho, Faradiba S. Serpa
Dátum:	2018
Megjegyzések:	The generalized additive model (GAM) is a standard statistical methodology and is frequently used in various fields of applied data analysis where the response variable is non-normal, e.g., integer-valued, and the explanatory variables are continuous, typically normally distributed. Standard assumptions of this model, among others, are that the explanatory variables are independent and identically distributed vectors which are not multicollinear. To handle the multicollinearity and serial dependence together a new hybrid model, called GAM-PCA-VAR model, was proposed in [17] (de Souza et al., J Roy Stat Soc C-Appl 2018) which is the combination of GAM with the principal component analysis (PCA) and the vector autoregressive (VAR) model. In this paper, some properties of the GAM-PCA-VAR model are discussed theoretically and verified by simulation. A real data set is also analyzed with the aim to describe the association between respiratory disease and air pollution concentrations.
ISBN:	978-3-319-96943-5
Tárgyszavak:	Természettudományok Matematika- és számítástudományok könyvfejezet Air pollution Generalized additive model Multicollinearity Principal component analysis Time series Vector autoregressive model
Megjelenés:	Time Series Analysis and Forecasting / Hrsg. Ignacio Rojas, Héctor Pomares, Olga Valenzuela. - p. 289-308. -
További szerzők:	Reisen, Valdério Anselmo Franco, Glaura C. Bondon, Pascal Cotta, Higor Henrique Aranda Filho, Paulo Roberto Prezotti Serpa, Faradiba S.
Pályázati támogatás:	EFOP-3.6.1-16-2016-00022 EFOP
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM093210
035-os BibID:	(WoS)000656909500005 (Scopus)85103972195
Első szerző:	Prezotti Filho, Paulo Roberto
Cím:	A periodic and seasonal statistical model for non-negative integer-valued time series with an application to dispensed medications in respiratory diseases / Paulo Roberto Prezotti Filho, Valderio Anselmo Reisen, Pascal Bondon, Márton Ispány, Milena Machado Melo, Faradiba Sarquis Serpa
Dátum:	2021
ISSN:	0307-904X
Megjegyzések:	This paper introduces a new class of models for non-negative integer-valued time series with a periodic and seasonal autoregressive structure. Some properties of the model are discussed and the conditional quasi-maximum likelihood method is used to estimate the parameters. The consistency and asymptotic normality of the estimators are established. Their performances are investigated for finite sample sizes and the empirical results indi- cate that the method gives accurate estimates. The proposed model is applied to analyse the daily number of antibiotic dispensing medication for the treatment of respiratory diseases, registered in a health center of Vitória, Brazil.
Tárgyszavak:	Természettudományok Matematika- és számítástudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Count time series Periodicity Seasonality Consistency Forecast Air pollution problems
Megjelenés:	Applied Mathematical Modelling. - 96 (2021), p. 545-558. -
További szerzők:	Reisen, Valdério Anselmo Bondon, Pascal Ispány Márton (1966-) (informatikus, matematikus) Melo, Milena Machado Serpa, Faradiba S.
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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