Results 31 to 40 of about 3,153,646 (349)
Diagnostics through Residual Plots in Binomial Regression Addressing Chemical Species Data
Mathematical Problems in Engineering, 2022 Binomial regression is used as a generalized linear model (GLM) in natural sciences to identify the covariate structure that is responsible for outcomes. It is very important to assess the adequacy and effectiveness of any model before its implementation.
Z. Hussain, A. Akbar
semanticscholar +1 more source
POISSON REGRESSION MODELS TO ANALYZE FACTORS THAT INFLUENCE THE NUMBER OF TUBERCULOSIS CASES IN JAVA
Barekeng, 2023 Tuberculosis is an infectious disease and one of the world's top 10 highest causes of mortality in Indonesia. Based on this fact, it is necessary to study what factors affect number of tuberculosis cases.
Yekti Widyaningsih +1 more
doaj +1 more source
Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models [PDF]
, 2020 Penalization of the likelihood by Jeffreys' invariant prior, or by a positive power thereof, is shown to produce finite-valued maximum penalized likelihood estimates in a broad class of binomial generalized linear models.
Firth, David, Kosmidis, Ioannis
core +2 more sources
A comparison of optimization solvers for log binomial regression including conic programming
Computational statistics (Zeitschrift), 2021 Relative risks are estimated to assess associations and effects due to their ease of interpretability, e.g., in epidemiological studies. Fitting log-binomial regression models allows to use the estimated regression coefficients to directly infer the ...
F. Schwendinger +2 more
semanticscholar +1 more source
BMC Medical Research Methodology, 2023 Background Fractures are rare events and can occur because of a fall. Fracture counts are distinct from other count data in that these data are positively skewed, inflated by excess zero counts, and events can recur over time.
Anower Hossain +5 more
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Generalized ridge estimator in negative binomial regression model
, 2021 The ridge estimator has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The negative binomial regression model (NBRM) is a well-known model in application when the response variable is a ...
N. Rashad, N. Hammood, Z. Algamal
semanticscholar +1 more source
Multiple inflated negative binomial regression for correlated multivariate count data
Dependence Modeling, 2022 This article aims to provide a method of regression for multivariate multiple inflated count responses assuming the responses follow a negative binomial distribution.
Mathews Joseph +3 more
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Binomial Regression with Misclassification
Biometrics, 2003 Summary. Motivated by a study of human papillomavirus infection in women, we present a Bayesian binomial regression analysis in which the response is subject to an unconstrained misclassification process. Our iterative approach provides inferences for the parameters that describe the relationships of the covariates with the response and for the ...
Paulino, Carlos Daniel +2 more
openaire +3 more sources
Barekeng, 2022 Traffic accidents that always increase along with the increasing population growth and the number of vehicles impact the national economy. The number of traffic accidents is a count data that a Poisson distribution can approximate. The Poisson regression
M Al Haris, Prizka Rismawati Arum
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A Study of Count Regression Models for Mortality Rate
Cauchy: Jurnal Matematika Murni dan Aplikasi, 2021 This paper discusses how overdispersed count data to be fit. Poisson regression model, Negative Binomial 1 regression model (NEGBIN 1) and Negative Binomial regression 2 (NEGBIN 2) model were proposed to fit mortality rate data.
Anwar Fitrianto
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