Results 1 to 10 of about 1,379,638 (144)
Count Data Time Series Modelling in Julia—The CountTimeSeries.jl Package and Applications
Entropy, 2021 A new software package for the Julia language, CountTimeSeries.jl, is under review, which provides likelihood based methods for integer-valued time series.
Manuel Stapper
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New Zealand Plant Protection, 2015 The plethora of hightech data collection methods available to the modern biologist presents opportunities but also challenges While tools such as automated camera traps can vastly increase the efficiency of data collection and storage allowing for the collection of massive amounts of photographic data extracting quantitative data from these images ...
Z.J. Lennon +3 more
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Zero-Dependent Bivariate Poisson Distribution with Applications
Mathematics, 2023 The bivariate Poisson model is the most widely used model for bivariate counts, and in recent years, several bivariate Poisson regression models have been developed in order to analyse two response variables that are possibly correlated. In this paper, a
Najla Qarmalah, Abdulhamid A. Alzaid
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Mathematics, 2021 In this paper, we review overdispersed Bayesian generalized spatial conditional count data models. Their usefulness is illustrated with their application to infant mortality rates from Colombian regions and by comparing them with the widely used Besag ...
Mabel Morales-Otero +1 more
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Health Psychology and Behavioral Medicine, 2021 Background Dependent variables in health psychology are often counts, for example, of a behaviour or number of engagements with an intervention. These counts can be very strongly skewed, and/or contain large numbers of zeros as well as extreme outliers ...
James A. Green
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Count data models for demographic data∗ [PDF]
Mathematical Population Studies, 1994 "This paper deals with the estimation of single equation models in which the counts are regressed on a set of observed individual characteristics such as age, gender, or nationality.... We propose a generalized event count model to simultaneously allow for a wide class of count data models and account for over- and underdispersion.
Winkelmann, Rainer, Zimmermann, Klaus F
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Mathematics, 2022 The large arcsine exponential dispersion model (LAEDM) is a class of three-parameter distributions on the non-negative integers. These distributions show the specific characteristics of being leptokurtic, zero-inflated, overdispersed, and skewed to the ...
Shaul K. Bar-Lev, Ad Ridder
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MODELLING THE DETERMINANTS OF ADOPTION OF MULTIPLE CLIMATE CHANGE COPING AND ADAPTATION STRATEGIES. A MICRO ANALYSIS OF SMALLHOLDER FARMERS IN NORTHERN GHANA [PDF]
Review of Agricultural and Applied Economics, 2020 Climate change coping and adaptation (CCCA) mechanisms have become more relevant in the north of Ghana where there is evidence of severe impacts of climate change and poverty.
Shaibu Baanni AZUMAH +2 more
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The discrete weighted exponential distribution and its applications [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2018 We propose a new discrete distribution namely the discrete weighted exponential (dWE) distribution. It is discretization of weighted exponential distribution.
Panpharisa Khongthip +2 more
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Journal of New Theory, 2021 The Poisson regression model is widely used for count data. This model assumes equidispersion. In practice, equidispersion is seldom reflected in data. However, in real-life data, the variance usually exceeds the mean.
Burcu Durmuş, Öznur İşçi Güneri
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