Finite Mixture Distribution Method to Model Vehicle Headways at Port Collector-Distributor Roads

2021 ◽  
Vol 147 (12) ◽  
pp. 04021084
Author(s):  
Xiafan Gan ◽  
Jinxian Weng ◽  
Jinbao Luo
Keyword(s):  
Mixture Distribution ◽  
Finite Mixture ◽  
Distribution Method

A Segmentation Model for the Targeted Marketing of Consumer Durables

1995 ◽  
Vol 32 (4) ◽  
pp. 463-469 ◽  
Author(s):  
Barry L. Bayus ◽  
Raj Mehta
Keyword(s):  
Mixture Distribution ◽  
Finite Mixture ◽  
Consumer Durables ◽  
Empirical Application ◽  
Household Characteristics ◽  
Household Data ◽  
Potential Consumer ◽  
Consumer Durable ◽  
Managerial Implications ◽  
Targeted Marketing

The authors use finite mixture distribution theory to develop a segmentation model for targeting potential consumer durable buyers. The model enables them to identify simultaneously durable replacer segments on the basis of household characteristics and product ages and determine which of the household characteristics are significant predictors of segment membership. Using household data for five home appliances, the authors present an empirical application of the model. They also discuss managerial implications and uses of this approach.

A finite mixture of two Weibull distributions for modeling the diameter distributions of rotated-sigmoid, uneven-aged stands

2001 ◽  
Vol 31 (9) ◽  
pp. 1654-1659 ◽  
Author(s):  
Lianjun Zhang ◽  
Jeffrey H Gove ◽  
Chuangmin Liu ◽  
William B Leak
Keyword(s):  
Model Fitting ◽  
Mixture Distribution ◽  
Finite Mixture ◽  
Diameter Distribution ◽  
Weibull Distributions ◽  
Forest Stands ◽  
Negative Exponential Function ◽  
Diameter Frequency Distribution ◽  
Negative Exponential ◽  
Diameter Distributions

The rotated-sigmoid form is a characteristic of old-growth, uneven-aged forest stands caused by past disturbances such as cutting, fire, disease, and insect attacks. The diameter frequency distribution of the rotated-sigmoid form is bimodal with the second rounded peak in the midsized classes, rather than a smooth, steeply descending, monotonic curve. In this study a finite mixture of two Weibull distributions is used to describe the diameter distributions of the rotated-sigmoid, uneven-aged forest stands. Four example stands are selected to demonstrate model fitting and comparison. Compared with a single Weibull or negative exponential function, the finite finite mixture model is the only one that fits the diameter distributions well and produces root mean square error at least four times smaller than the other two. The results show that the finite mixture distribution is a better alternative method for modeling the diameter distribution of the rotated-sigmoid, uneven-aged forest stands.

scholarly journals Sequential Test for a Mixture of Finite Exponential Distribution

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
A.S. Al-Moisheer
Keyword(s):  
Mixture Distribution ◽  
Testing Procedure ◽  
Optimal Number ◽  
Finite Mixture ◽  
Sequential Test ◽  
Ratio Test ◽  
Test Statistic ◽  
General Hypothesis ◽  
Number Of Components ◽  
Exponential Mixture

Testing the number of components in a finite mixture is considered one of the challenging problems. In this paper, exponential finite mixtures are used to determine the number of components in a finite mixture. A sequential testing procedure is adopted based on the likelihood ratio test (LRT) statistic. The distribution of the test statistic under the null hypothesis is obtained using a resampling technique based on B bootstrap samples. The quantiles of the distribution of the test statistic are evaluated from the B bootstrap samples. The performance of the test is examined through the empirical power and application on two real datasets. The proposed procedure is not only used for testing the number of components but also for estimating the optimal number of components in a finite exponential mixture distribution. The innovation of this paper is the sequential test, which tests the more general hypothesis of a finite exponential mixture of k components versus a mixture of k + 1 components. The special case of testing an exponential mixture of one component versus two components is the one commonly used in the literature.

A finite mixture distribution for modelling multinomial extra variation

Biometrika ◽  
1993 ◽  
Vol 80 (2) ◽  
pp. 363-371 ◽  
Author(s):  
JORGE G. MOREL ◽  
NEERCHAL K. NAGARAJ
Keyword(s):  
Mixture Distribution ◽  
Finite Mixture

Finite Mixture Examples; MAPIS Details

2017 ◽  
Author(s):  
Russell Cheng
Keyword(s):  
Sample Size ◽  
Importance Sampling ◽  
Mixture Distribution ◽  
Finite Mixture ◽  
Practical Implementation ◽  
Posterior Distributions ◽  
Normal Mixture ◽  
Data Set ◽  
Numerical Examples ◽  
Normal Mixture Models

Two detailed numerical examples are given in this chapter illustrating and comparing mainly the reversible jump Markov chain Monte Carlo (RJMCMC) and the maximum a posteriori/importance sampling (MAPIS) methods. The numerical examples are the well-known galaxy data set with sample size 82, and the Hidalgo stamp issues thickness data with sample size 485. A comparison is made of the estimates obtained by the RJMCMC and MAPIS methods for (i) the posterior k-distribution of the number of components, k, (ii) the predictive finite mixture distribution itself, and (iii) the posterior distributions of the component parameters and weights. The estimates obtained by MAPIS are shown to be more satisfactory and meaningful. Details are given of the practical implementation of MAPIS for five non-normal mixture models, namely: the extreme value, gamma, inverse Gaussian, lognormal, and Weibull. Mathematical details are also given of the acceptance-rejection importance sampling used in MAPIS.

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