Zobrazeno 1 - 10
of 343
pro vyhledávání: '"F. Sellers"'
Autor:
B. Lledo, A. Fuentes, F. M. Lozano, A. Cascales, R. Morales, M. Hortal, F. Sellers, A. Palacios-Marques, R. Bermejo, F. Quereda, J. C. Martínez-Escoriza, R. Bernabeu, A. Bernabeu
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract The factors that cause a preterm birth (PTB) are not completely understood up to date. Moreover, PTB is more common in pregnancies achieved by in-vitro fertilization (IVF) than in spontaneous pregnancies. Our aim was to compare the compositi
Externí odkaz:
https://doaj.org/article/20b9ff50db8a40dfbddc611ef8dfea39
Publikováno v:
Stats, Vol 5, Iss 1, Pp 52-69 (2022)
Clustered count data are commonly modeled using Poisson regression with random effects to account for the correlation induced by clustering. The Poisson mixed model allows for overdispersion via the nature of the within-cluster correlation, however,
Externí odkaz:
https://doaj.org/article/24209c5e0f134699aa9b0a5ae753d0b9
Autor:
Kimberly F. Sellers
While the Poisson distribution is a classical statistical model for count data, the distributional model hinges on the constraining property that its mean equal its variance. This text instead introduces the Conway-Maxwell-Poisson distribution and mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d81e45b0354b27d7b96692cec533618c
https://doi.org/10.1017/9781108646437
https://doi.org/10.1017/9781108646437
Publikováno v:
Communications in Statistics - Theory and Methods. 52:4692-4718
The bivariate Poisson distribution is a natural choice for modeling bivariate count data. Its constraining assumption, however, limits model flexibility in some contexts. This work considers the tr...
Publikováno v:
Journal of Statistical Computation and Simulation. 91:1815-1845
Count data with inflated zeros commonly occur in numerous research studies. Accordingly, there is substantive literature regarding zero-inflated Poisson and analogous generalizable count regression...
Publikováno v:
Journal of Time Series Analysis. 41:436-453
Integer‐valued time series data have an ever‐increasing presence in various applications (e.g., the number of purchases made in response to a marketing strategy, or the number of employees at a business) and need to be analyzed properly. While a
Autor:
Kimberly F. Sellers, Derek S. Young
Publikováno v:
Journal of Statistical Computation and Simulation. 89:1649-1673
While excess zeros are often thought to cause data over-dispersion (i.e. when the variance exceeds the mean), this implication is not absolute. One should instead consider a flexible class of distr...
Publikováno v:
Stats
Volume 4
Issue 2
Pages 21-326
Stats, Vol 4, Iss 21, Pp 308-326 (2021)
Volume 4
Issue 2
Pages 21-326
Stats, Vol 4, Iss 21, Pp 308-326 (2021)
Multivariate count data are often modeled via a multivariate Poisson distribution, but it contains an underlying, constraining assumption of data equi-dispersion (where its variance equals its mean). Real data are oftentimes over-dispersed and, as su
Publikováno v:
Journal of Statistical Distributions and Applications, Vol 8, Iss 1, Pp 1-12 (2021)
Al-Osh and Alzaid (1988) consider a Poisson moving average (PMA) model to describe the relation among integer-valued time series data; this model, however, is constrained by the underlying equi-dispersion assumption for count data (i.e., that the var
Autor:
Kimberly F. Sellers
While the Poisson distribution is a classical statistical model for count data, the distributional model hinges on the constraining property that its mean equal its variance. This text instead introduces the Conway-Maxwell-Poisson distribution and mo