Results 151 to 160 of about 2,674 (172)

ANALYTICAL APPROXIMATION OF EXACT POISSON-LOGNORMAL LIKELIHOOD FUNCTIONS

Health Physics, 2008
Simple analytical approximations of exact Poisson-lognormal likelihood functions are obtained numerically. The Poisson-lognormal statistical model describes counting measurements with lognormally distributed normalization factors. The analytical expressions for the likelihood function allow maximum likelihood data fitting using nonlinear-least-squares ...
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Predicting future consumer purchases in grocery retailing with the condensed Poisson lognormal model

Journal of Retailing and Consumer Services, 2022
Abstract To identify the effect of marketing actions on consumer purchasing, analysts must disentangle the dynamic component of purchasing from expected period-to-period stochastic fluctuations. This is done by comparing marketplace observations to the conditional expectation of future purchasing.
Giang Trinh, Malcolm J. Wright
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The spatio-temporal multivariate Poisson lognormal model

AIP Conference Proceedings, 2018
To deal with the variation and correlation structure of accident data along with recognized covariate effects, we develop a spatio-temporal model for multivariate accident count data. Based on the multivariate Poisson lognormal model, we introduce linear combinations of random impulses to capture spatial correlation.
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Multivariate Poisson-Lognormal Models for Jointly Modeling Crash Frequency by Severity

Transportation Research Record: Journal of the Transportation Research Board, 2007
A new multivariate approach is introduced for jointly modeling data on crash counts by severity on the basis of multivariate Poisson-lognormal models. Although the data on crash frequency by severity are multivariate in nature, they have often been analyzed by modeling each severity level separately, without taking into account correlations that exist ...
Eun Sug Park, Dominique Lord
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Maximum likelihood fitting of the Poisson lognormal distribution

Environmental and Ecological Statistics, 2007
In this paper some properties and analytic expressions regarding the Poisson lognormal distribution such as moments, maximum likelihood function and related derivatives are discussed. The author provides a sharp approximation of the integrals related to the Poisson lognormal probabilities and analyzes the choice of the initial values in the fitting ...
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Retention for Stoploss reinsurance to minimize VaR in compound Poisson-Lognormal distribution

AIP Conference Proceedings, 2015
Automobile insurance is one of the emerging general insurance’s product in Indonesia. Fluctuation in total premium revenues and total claim expenses leads to a risk that insurance company can not be able to pay consumer’s claims, thus reinsurance is needeed.
Achmad Zanbar Soleh, Lienda Noviyanti, Irma Nurrahmawati   +2 more
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Poisson-Lognormal Distributions

2018
The Poisson-lognormal distribution was suggested as a model for commonness of species by Preston. The analysis leading him to suggest this distribution was as follows: Suppose that the number of each species caught in a trap is assumed to be a single sample from a Poisson distribution with mean λ. R. S. Uhler and P. G.
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Density approximations and VaR computation for compound Poisson-lognormal distributions

Communications in Statistics - Simulation and Computation, 2015
ABSTRACTParametric approximations of the compound Poisson-lognormal distribution are developed and used to compute Value-at-Risk (VaR). As guidelines for finding an approximation, the skewness–kurtosis space and the tail behavior are considered. The Generalized Beta distribution of the second kind (GB2) and a mixture of lognormals are found to provide ...
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Critical elements on fitting the Bayesian multivariate Poisson Lognormal model

AIP Conference Proceedings, 2015
Motivated by a problem on fitting multivariate models to traffic accident data, a detailed discussion of the Multivariate Poisson Lognormal (MPL) model is presented. This paper reveals three critical elements on fitting the MPL model: the setting of initial estimates, hyperparameters and tuning parameters.
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Bayesian Multivariate Poisson Lognormal Models for Crash Severity Modeling and Site Ranking

Transportation Research Record: Journal of the Transportation Research Board, 2009
Traditionally, highway safety analyses have used univariate Poisson or negative binomial distributions to model crash counts for different levels of crash severity. Because unobservables or omitted variables are shared across severity levels, however, crash counts are multivariate in nature.
Jonathan Aguero-Valverde, Paul P. Jovanis   +1 more
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