Results 281 to 290 of about 3,733,122 (330)
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Sparse Bayesian Learning-Based Kernel Poisson Regression
IEEE Transactions on Cybernetics, 2019In this paper, we introduce a closed-form sparse Bayesian kernel Poisson regression (SBKPR) model for count data regression problems based on the sparse Bayesian learning (SBL) approach.
Yuheng Jia +4 more
semanticscholar +1 more source
, 2019
Statistical modelling of road crashes has been of extreme interest to researchers over the last decades. Such models are necessary for the investigation of the opportunities for road safety improvement.
G. Abdella +3 more
semanticscholar +1 more source
Statistical modelling of road crashes has been of extreme interest to researchers over the last decades. Such models are necessary for the investigation of the opportunities for road safety improvement.
G. Abdella +3 more
semanticscholar +1 more source
A new adjusted Liu estimator for the Poisson regression model
Concurrency and Computation, 2021Muhammad Amin, M. Akram, B. M. G. Kibria
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Subset Selection in Poisson Regression
Journal of Statistical Theory and Practice, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sakate, D. M. +2 more
openaire +2 more sources
1992
It is well-known among applied researchers that the assumption of equality of conditional mean and variance in the Poisson model is rather restrictive, especially that there is a tendency for too low standard errors in case of overdispersion. Pre-tests or more general models have been proposed to solve the problem.
Rainer Winkelmann, Klaus F. Zimmermann
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It is well-known among applied researchers that the assumption of equality of conditional mean and variance in the Poisson model is rather restrictive, especially that there is a tendency for too low standard errors in case of overdispersion. Pre-tests or more general models have been proposed to solve the problem.
Rainer Winkelmann, Klaus F. Zimmermann
openaire +1 more source
1996
Abstract To summarize the different approaches to statistical inference and decisionmaking, an analogy with practice in the medical profession may be useful. This profession has an accumulated knowledge of many diseases - the statistical models. A task of the doctor is to discover which one applies to a particular patient.
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Abstract To summarize the different approaches to statistical inference and decisionmaking, an analogy with practice in the medical profession may be useful. This profession has an accumulated knowledge of many diseases - the statistical models. A task of the doctor is to discover which one applies to a particular patient.
openaire +1 more source
2001
Abstract Counts of brain cancer incidence cases and deaths were recorded as part of the Surveillance, Epidemiology, and End Results (SEER) program of the Bio metry Branch of the National Cancer Institute. The SEER program acquired these incidence data from a number of surveyed areas in the United States (for example, the state of ...
openaire +1 more source
Abstract Counts of brain cancer incidence cases and deaths were recorded as part of the Surveillance, Epidemiology, and End Results (SEER) program of the Bio metry Branch of the National Cancer Institute. The SEER program acquired these incidence data from a number of surveyed areas in the United States (for example, the state of ...
openaire +1 more source