Results 31 to 40 of about 14,479,772 (204)

Generalized Poisson Shock Models

open access: yesThe Annals of Probability, 1981
Suppose that shocks hit a device in accordance with a nonhomogeneous Poisson process with intensity function $\lambda(t)$. The $i^{th}$ shock has a value $X_i$ attached to it. The $X_i$ are assumed to be independent and identically distributed positive random variables, and are also assumed independent of the counting process of shocks.
openaire   +2 more sources

Poisson Model To Generate Isotope Distribution for Biomolecules [PDF]

open access: yesJournal of Proteome Research, 2017
We introduce a simplified computational algorithm for computing isotope distributions (relative abundances and masses) of biomolecules. The algorithm is based on Poisson approximation to binomial and multinomial distributions. It leads to a small number of arithmetic operations to compute isotope distributions of molecules.
openaire   +2 more sources

D-optimal designs for Poisson regression models [PDF]

open access: yes, 2008
We consider the problem of finding an optimal design under a Poisson regression model with a log link, any number of independent variables and an additive linear predictor.
Woods, D.C.   +3 more
core   +1 more source

PERBANDINGAN REGRESI BINOMIAL NEGATIF DAN REGRESI GENERALISASI POISSON DALAM MENGATASI OVERDISPERSI (Studi Kasus: Jumlah Tenaga Kerja Usaha Pencetak Genteng di Br. Dukuh, Desa Pejaten)

open access: yesE-Jurnal Matematika, 2014
Poisson regression is a nonlinear regression that is often used to model count response variable and categorical, interval, or count regressor. This regression assumes equidispersion, i.e., the variance equals the mean.
NI MADE RARA KESWARI   +2 more
doaj   +1 more source

PB-Steric Equations: A General Model of Poisson–Boltzmann Equations

open access: yesSIAM Journal on Applied Mathematics, 2023
When ions are crowded, the effect of steric repulsion between ions (which can produce oscillations in charge density profiles) becomes significant and the conventional Poisson-Boltzmann (PB) equation should be modified. Several modified PB equations were developed but the associated total ionic charge density has no oscillation.
Jhih-Hong Lyu, Tai-Chia Lin
openaire   +3 more sources

Poisson algebras via model theory and differential-algebraic geometry [PDF]

open access: yes, 2017
Brown and Gordon asked whether the Poisson Dixmier–Moeglin equivalence holds for any complex affine Poisson algebra, that is, whether the sets of Poisson rational ideals, Poisson primitive ideals, and Poisson locally closed ideals coincide.
Moosa, Rahim   +8 more
core   +1 more source

Modeling with generalized linear model on covid-19: Cases in Indonesia

open access: yesInternational Journal of Electronics and Communications System, 2021
The ongoing Covid-19 outbreak has made scientists continue to research this Covid-19 case. Most of the research carried out is on the prediction and modeling of Covid-19 data. This study will also discuss Covid-19 data modeling.
Subian Saidi   +2 more
doaj   +1 more source

Spatial modeling of data with excessive zeros applied to reindeer pellet‐group counts

open access: yesEcology and Evolution, 2016
We analyze a real data set pertaining to reindeer fecal pellet‐group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation.
Youngjo Lee   +4 more
doaj   +1 more source

Locally A-optimal Design for Poisson Regression Model with Two Parameters [PDF]

open access: yesThe Egyptian Statistical Journal
Generalized linear model (GLM) which is regarded as an extension of standard linear regression in that it allows continuous or discrete data from one-parameter exponential family distributions to be paired with explanatory variables using appropriate ...
Tofan Biswal
doaj   +1 more source

A Multivariate Poisson Deep Learning Model for Genomic Prediction of Count Data

open access: yesG3: Genes, Genomes, Genetics, 2020
The paradigm called genomic selection (GS) is a revolutionary way of developing new plants and animals. This is a predictive methodology, since it uses learning methods to perform its task.
Osval Antonio Montesinos-López   +6 more
doaj   +1 more source

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