Results 31 to 40 of about 1,308 (195)
Generalized mixed linear modeling approach to analyze nodulation in common bean inbred lines [PDF]
Pesquisa Agropecuária Brasileira, 2017 : The objective of this work was to compare distributions for the modeling of the number and dry matter weight of nodules (DWN) of Rhizobium from different inoculants in common bean (Phaseolus vulgaris) inbred lines subjected to nitrogen doses, as well ...
Diego Ary Rizzardi +5 more
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Stationary underdispersed INAR(1) models based on the backward approach
Revstat Statistical Journal, 2021 Most of the stationary first-order autoregressive integer-valued (INAR(1)) models were developed for a given thinning operator using either the forward approach or the backward approach. In the forward approach the marginal distribution of the time series is specified and an appropriate distribution for the innovation sequence is sought. Whereas in the
Emad-Eldin A. A. Aly, Nadjib Bouzar
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A Correction for an Underdispersed Event Count Probability Distribution [PDF]
Political Analysis, 1993 We demonstrate that the expected value and variance commonly given for a well-known probability distribution are incorrect. We also provide corrected versions and report changes in a computer program to account for the known practical uses of this distribution.The probability distribution in question, named the continuous parameter binomial (CPB) by ...
Rainer Winkelmann +2 more
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A Weighted Poisson Distribution for Underdispersed Count Data
International Journal of Statistics and Probability, 2021 In this paper, we present a new weighted Poisson distribution for modeling underdispersed count data. Weighted Poisson distribution occurs naturally in contexts where the probability that a particular observation of Poisson variable enters the sample gets multiplied by some non-negative weight function.
Chedly Gelin Louzayadio +2 more
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Estimating polymorphic growth curve sets with nonchronological data
Ecology and Evolution, 2020 When we collect the growth curves of many individuals, orderly variation in the curves is often observed rather than a completely random mixture of various curves.
Kai Moriguchi
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Mean and Variance Modeling of Under- and Overdispersed Count Data
Journal of Statistical Software, 2016 This article describes the R package CountsEPPM and its use in determining maximum likelihood estimates of the parameters of extended Poisson process models.
David M. Smith, Malcolm J. Faddy
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Journal of Biostatistics and Epidemiology, 2023 Introduction: Although geometric distribution, which is a special case of Negative Binomial (NB) distribution, also belongs to the discrete family of distributions, little attention has been paid to modeling count data with the geometric distribution ...
Zainab Al-Balushi +2 more
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Approaches to Detecting and Modeling Over-and Underdispersion in Alternative Count Data Distributions and an Application of Logistic Regression and Random Forest Modeling to Improve Screening Tools for Tic Disorders in Children [PDF]
, 2023 This dissertation focuses on theory and application of discrete data methods, particularly approaches to over- and underdispersion relative to the Poisson distribution and an application of random forest and logistic regression modeling.
Wardrop, Rebecca C.
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Bio-based and Applied Economics, 2014 Soil and water conservation practices are being promoted in Ghana as a way of sustainably managing the environment to support agricultural production. Despite the important role the adoption of the practices plays in conserving the environment, very few ...
Paul Nkegbe, Bhavani Shankar
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Some developments on seasonal INAR processes with application to influenza data
Scientific Reports, 2023 Influenza epidemic data are seasonal in nature. Zero-inflation, zero-deflation, overdispersion, and underdispersion are frequently seen in such number of cases of disease (count) data.
Fatimah E. Almuhayfith +4 more
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