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Approximate Bayes Estimation for Log-Dagum Distribution
2019
Cumhuriyet Science Journal
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In this article, the approximate Bayes estimation problem for the log-Dagum distribution with three parameters is considered. ...
A Monte-Carlo simulation study is performed to compare performances of maximum likelihood and approximate Bayes estimators in terms of mean square errrors and biases. ...
The biases and MSEs of ML and approximate bayes estimators for unknown
parameters at different samples sizes as
100,
200,500,1000
n
are given in Table1. ...
doi:10.17776/csj.484730
fatcat:eu2tfr2kinh43pdgfe3tohw47m
Classification: Oldtimers and newcomers
1989
Journal of Chemometrics
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DATAI
In the well-determined situation LDA is a better candidate than QDA because it estimates less parameters. In the ill-posed case they both give bad prediction. ...
x — Xx)] 7/ en + y In ej —2 In m% (7) j=1 j=1
The eigenvalue estimates calculated from the sample covariance matrix are biased; the largest ones are biased high and the smallest ones are biased toward ...
doi:10.1002/cem.1180030304
fatcat:rt4qnozxdngwpnvhekptml57ka
Page 474 of Journal of Chemometrics Vol. 3, Issue 3
[page]
1989
Journal of Chemometrics
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In ill-posed cases biasing is the only way to reduce the high variance of the estimates. ...
No method is better than LDA in the WINE17 data set. RDA also chooses the pure linear model. Both SIMCA and DASCO estimate too many parameters, hence give worse classification. ...
Signal Parameters Estimation Using Time-Frequency Representation For Laser Doppler Anemometry
2012
Zenodo
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Publication in the conference proceedings of EUSIPCO, Bucharest, Romania, 2012 ...
In [2] , the wavelet estimator reaches the CRB for the Doppler frequency estimation for an SNR higher than 4 dB. For the burst width, the estimator is biased. ...
The problem of parameter estimation of LDA signals has received a great deal of attention [1] , [2] , [3] . ...
doi:10.5281/zenodo.52201
fatcat:7nyl65itpzf4plof4tzq3qzbuu
Regularized Discriminant Analysis
1989
Journal of the American Statistical Association
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Alternatives to the usual maximum likelihood (plug-in) estimates for the covariance matrices are proposed. ...
These alternatives are characterized by two parameters, the values of which are customized to individual situations by jointly minimizing a sample-based estimate of future misclassification risk. ...
highly biases the covariance matrix estimates. ...
doi:10.1080/01621459.1989.10478752
fatcat:rh6upzcenvdwjnh5hzvs2qll5a
Training Deformable Part Models with Decorrelated Features
2013
2013 IEEE International Conference on Computer Vision
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How important is joint parameter estimation? How many negative images are needed for training?). ...
In this paper, we show how to train a deformable part model (DPM) fast-typically in less than 20 minutes, or four times faster than the current fastest method-while maintaining high average precision on ...
These parameters were estimated on PASCAL VOC 2010 trainval. ...
doi:10.1109/iccv.2013.375
dblp:conf/iccv/GirshickM13
fatcat:s4o4likgxfgq7jb6274my5l7wa
Regularized Discriminant Analysis
1989
Journal of the American Statistical Association
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Alternatives to the usual maximum likelihood (plug-in) estimates for the covariance matrices are proposed. ...
These alternatives are characterized by two parameters, the values of which are customized to individual situations by jointly minimizing a sample based estimate of future misclassification risk. ...
In
I
the classification
It is well known that the estimates based on Eq. (12) produce biased estimates of the eigenvalues; the largest ones are biased high and the smallest ones are biased towards ...
doi:10.2307/2289860
fatcat:mk54a2azorfynkmzzycza7ii3e
Using BS-PSD-LDA approach to measure operational risk of Chinese commercial banks
2012
Economic Modelling
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Using hand-collected samples of 426 operational losses in Chinese commercial banks during 1994-2010, we estimate the magnitude of operational losses using the BS-PSD-LDA method. ...
To address these issues, this paper puts forward a loss distribution approach (LDA) based on bootstrap sampling and piecewise-defined severity distribution (BS-PSD-LDA). ...
Acknowledgment This research described in this paper was substantially supported by a program (No. ...
doi:10.1016/j.econmod.2012.06.031
fatcat:h4adxi23xbhdlnh6glk4gqhbry
Assimilation of microwave brightness temperature in a land data assimilation system with multi-observation operators
2013
Journal of Geophysical Research - Atmospheres
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It was demonstrated that the BMA scheme with LDAS-MO has the potential to estimate soil moisture with high accuracy. ...
It was found that the assimilated volumetric soil-water content using each of the three observation operators improved the estimation of soil moisture content in the top soil layer (0-10 cm), with reduced ...
Steve Ghan and the three anonymous reviewers for constructive comments and suggestions, which have helped us in improving the paper. ...
doi:10.1002/jgrd.50377
fatcat:gcvdhnnjerafnmphbsecy6ndpq
Regularization studies of linear discriminant analysis in small sample size scenarios with application to face recognition
2005
Pattern Recognition Letters
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In this paper, we propose a new LDA method that attempts to address the SSS problem using a regularized FisherÕs separability criterion. ...
In addition, a scheme of expanding the representational capacity of face database is introduced to overcome the limitation that the LDA-based algorithms require at least two samples per class available ...
Portions of the research in this paper use the FERET database of facial images collected under the FERET program (Phillips et al., 1998) . ...
doi:10.1016/j.patrec.2004.09.014
fatcat:6kur3v3hinhpndyb7d7zx7fyeu
Estimation of EPMC for High-dimensional Data(Session 3b)
2011
Proceedings of the Symposium of Japanese Society of Computational Statistics
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derived by Kubokawa, Hyode and Srivastava (2011), and the second-order unbiased estimator of EMPC is also g{ven, In this study the estimation accuracy of the second-order unbiased estirnaterof EPMC is ...
Since the inverse ef the sarnple cevariance matrix is close to an ill condition in this situation. it may be better to replace it with the inverse of the ridge-type estimator of the covariance matrix in ...
Research of the second author was supported in part by Grant-in-Aid for Scientific Research (21540114 and 23243039) from Japan Society for the Promotion of Science. ...
doi:10.20551/jscssymo.25.0_115
fatcat:pdl3dot3qnddxoblkpimt6fxvy
Page 823 of The Journal of the Operational Research Society Vol. 54, Issue 8
[page]
2003
The Journal of the Operational Research Society
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parameter estimates, but the use of classical linear discriminant analysis (LDA) will. ...
parameters in Equation (4) are biased and inconsistent because the final term in Equation (4) has been omitted from the estimation of Equation (1). ...
Transcriptome-wide association studies accounting for colocalization using Egger regression
2018
Genetic Epidemiology
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In contrast, LD-aware MR-Egger (LDA MR-Egger) regression can control type I error in this case while attaining similar power as other methods in situations where these provide valid tests. ...
We derive the standard TWAS approach in the context of MR and show in simulations that the standard TWAS does not control type I error for causal gene identification when eQTLs have pleiotropic or LD-confounded ...
All studies and funders are listed in Michailidou et al (2017) . ...
doi:10.1002/gepi.22131
pmid:29808603
pmcid:PMC6342197
fatcat:u5xjgzx6wvazhlt266vmnzkdme
Learning Supervised Topic Models for Classification and Regression from Crowds
2017
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In this article, we propose two supervised topic models, one for classification and another for regression problems, which account for the heterogeneity and biases among different annotators that are encountered ...
in practice when learning from crowds. ...
The only parameters left to estimate are then the regression coefficients h and the annotators biases, b ¼ fb r g R r¼1 , and precisions, p ¼ fp r g R r¼1 , which we estimate using variational Bayesian ...
doi:10.1109/tpami.2017.2648786
pmid:28103190
fatcat:ur4og7l2mzd4fm45fjdu5s5e3i
Development of the Coupled Atmosphere and Land Data Assimilation System (CALDAS) and Its Application Over the Tibetan Plateau
2012
IEEE Transactions on Geoscience and Remote Sensing
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CAL-DAS also improved biases in cloud conditions and associated rainfall events, which contaminated land surface conditions in LDAS-A. ...
Land surface heterogeneities are important for accurate estimation of land-atmosphere interactions and their feedbacks on water and energy budgets. ...
Ohta, Data Archiving Managers of the Coordinated Energy and Water Cycle Observation Project, The University of Tokyo, for their continued support in the model validations; Japan Aerospace Exploration Agency ...
doi:10.1109/tgrs.2012.2190517
fatcat:7q5oiflwr5hlnmlbgklsnd76d4
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