نتایج جستجو برای: maximum likelihood classifier

تعداد نتایج: 398600  

2014
Xiaoshan Wang

The maximum likelihood estimation (MLE) method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM) approach is developed...

2014
Christos P. Kitsos Vassilios G. Vassiliadis Thomas L. Toulias

The introduced three parameter (position μ, scale Σ and shape γ) multivariate generalized Normal distribution (γ-GND) is based on a strong theoretical background and emerged from Logarithmic Sobolev Inequalities. It includes a number of well known distributions such as the multivariate Uniform, Normal, Laplace and the degenerated Dirac distributions. In this paper, the cumulative distribution, ...

Journal: :Science 2006
Rampal S Etienne Andrew M Latimer John A Silander Richard M Cowling

Latimer et al. (Reports, 9 September 2005, p. 1722) used an approximate likelihood function to estimate parameters of Hubbell's neutral model of biodiversity. Reanalysis with the exact likelihood not only yields different estimates but also shows that two similar likelihood maxima for very different parameter combinations can occur. This reveals a limitation of using species abundance data to g...

Journal: :The international journal of biostatistics 2012
Jordan Brooks Mark J van der Laan Alan S Go

Estimators of the conditional expectation, i.e., prediction, function involve a global bias-variance trade off. In some cases, an estimator that yields unbiased estimates of the conditional expectation for a particular partitioning of the data may be desirable. Such estimators are calibrated with respect to the partitioning. We identify the conditional expectation given a particular partitionin...

Journal: :Biometrika 2009
Donglin Zeng Qingxia Chen Joseph G Ibrahim

We propose a class of transformation models for multivariate failure times. The class of transformation models generalize the usual gamma frailty model and yields a marginally linear transformation model for each failure time. Nonparametric maximum likelihood estimation is used for inference. The maximum likelihood estimators for the regression coefficients are shown to be consistent and asympt...

Journal: :Molecular biology and evolution 2010
Edward Susko

The most frequent measure of phylogenetic uncertainty for splits is bootstrap support. Although large bootstrap support intuitively suggests that a split in a tree is well supported, it has not been clear how large bootstrap support needs to be to conclude that there is significant evidence that a hypothesized split is present. Indeed, recent work has shown that bootstrap support is not first-o...

Journal: :international journal of agricultural management and development 2012
agom damian ila susan ben ohen kingsley okoi itam nyambi n. inyang

the technical efficiency involved in cocoa production in cross river state was estimated using the stochastic frontier production function analysis. the effects of some selected socio- economic characteristics of the farmers on the efficiency indices were also estimated. the study relied upon primary data generated from interviewing cocoa farmers using a set of structured questionnaire. a multi...

Journal: :پژوهش های علوم و فناوری چوب و جنگل 0

in order to capability investigation on landsat-7 satellite etm+ data in separability forest type and mapping in the zagros region, a small window digital data dating july 2001 from ghalajeh forests in the kermanshah province were analyzed. ground data were provided the cluster sampling method and with 0.36 ha. no radiometric error was found then the quality investigations. orthorectification w...

Journal: :Journal of Research of the National Institute of Standards and Technology 2011

2007
David Faraggi Richard Simon

SUMMARY Neural networks have received considerable attention in recent years. This development has been pursued primarily by non-statisticians. Consequently many statistical tools and concepts have not been utilized in this development and great claims for neural networks have sometimes been made without comparisons to standard statistical procedures. In this paper we utilize the input-output r...

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