Works about FINITE mixture models (Statistics)
Results: 334
HETEROGENEITY OF AMBIGUITY PREFERENCES.
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- Review of Economics & Statistics, 2014, v. 96, n. 4, p. 609, doi. 10.1162/REST_a_00392
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A New Separation Index and Classification Techniques Based on Shannon Entropy.
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- Methodology & Computing in Applied Probability, 2023, v. 25, n. 4, p. 1, doi. 10.1007/s11009-023-10055-w
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Adaptive Rejection Metropolis Simulated Annealing for Detecting Global Maximum Regions.
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- Methodology & Computing in Applied Probability, 2016, v. 18, n. 1, p. 1, doi. 10.1007/s11009-014-9395-6
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Cluster analysis of post-landfall tracks of landfalling tropical cyclones over China.
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- Climate Dynamics, 2013, v. 40, n. 5/6, p. 1237, doi. 10.1007/s00382-012-1519-5
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Bayesian Spatial Homogeneity Pursuit of Functional Data: An Application to the U.S. Income Distribution.
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- Bayesian Analysis, 2023, v. 18, n. 2, p. 579, doi. 10.1214/22-BA1320
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Contributed comment on Article by Wade and Ghahramani.
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- Bayesian Analysis, 2018, v. 13, n. 2, p. 601
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Invited comment on Article by Wade and Ghahramani.
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- Bayesian Analysis, 2018, v. 13, n. 2, p. 594
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A Comparison of Truncated and Time-Weighted Plackett-Luce Models for Probabilistic Forecasting of Formula One Results.
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- Bayesian Analysis, 2018, v. 13, n. 2, p. 335, doi. 10.1214/17-BA1048
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MODELE DAYALI KÜMELEME ANALİZİNDE OPTİMUM KÜMELEME İÇİN YENİ BİR YAKLAŞIM.
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- SDU Journal of Engineering Sciences & Design / Mühendislik Bilimleri ve Tasarım Dergisi, 2020, v. 8, n. 5, p. 218, doi. 10.21923/jesd.828051
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MODELE DAYALI KÜMELEME ANALİZİNDE OPTİMUM KÜMELEME İÇİN YENİ BİR YAKLAŞIM.
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- SDU Journal of Engineering Sciences & Design / Mühendislik Bilimleri ve Tasarım Dergisi, 2020, v. 8, p. 218, doi. 10.21923/jesd.828051
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Characterizing bovine adipocyte distribution and its relationship with carcass and meat characteristics using a finite mixture model.
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- Journal of Animal Science, 2012, v. 90, n. 9, p. 2995, doi. 10.2527/jas.2011-4838
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THE SPANISH PUBLIC PENSION SYSTEM: THE QUEST FOR FINANCIAL SUSTAINABILITY AND EQUITY.
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- Revista de Economía Aplicada, 2018, v. 26, n. 76, p. 133
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ORGANIZATION OF PRODUCTION AND THE DISTRIBUTION OF LABOR INCOME IN SPAIN.
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- Revista de Economía Aplicada, 2018, v. 26, n. 76, p. 101
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THE GREAT RECESSION: THE WORST EVER?
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- Revista de Economía Aplicada, 2018, v. 26, n. 76, p. 73
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Comparison of Statistical Approaches for Reconstructing Random Coefficients in the Problem of Stochastic Modeling of Air–Sea Heat Flux Increments.
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- Mathematics (2227-7390), 2024, v. 12, n. 2, p. 288, doi. 10.3390/math12020288
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Classification Methods for the Serological Status Based on Mixtures of Skew-Normal and Skew-t Distributions.
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- Mathematics (2227-7390), 2024, v. 12, n. 2, p. 217, doi. 10.3390/math12020217
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Statistical Inference on a Finite Mixture of Exponentiated Kumaraswamy-G Distributions with Progressive Type II Censoring Using Bladder Cancer Data.
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- Mathematics (2227-7390), 2022, v. 10, n. 15, p. 2800, doi. 10.3390/math10152800
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Statistical Feature Construction for Forecasting Accuracy Increase and Its Applications in Neural Network Based Analysis.
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- Mathematics (2227-7390), 2022, v. 10, n. 4, p. N.PAG, doi. 10.3390/math10040589
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Upper bound for variance of finite mixtures of power exponential distributions.
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- Mathematica Slovaca, 2022, v. 72, n. 3, p. 807, doi. 10.1515/ms-2022-0055
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Finite Mixture Model: Prediction of Time Series Data Using Bayesian Method.
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- Malaysian Journal of Mathematical Sciences, 2022, v. 16, n. 2, p. 175, doi. 10.47836/mjms.16.2.01
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Mixture Modeling: Applications in Educational Psychology.
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- Educational Psychologist, 2016, v. 51, n. 3/4, p. 354, doi. 10.1080/00461520.2016.1207176
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Full-model estimation for non-parametric multivariate finite mixture models.
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- Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2024, v. 86, n. 4, p. 896, doi. 10.1093/jrsssb/qkae002
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Non-parametric identification and estimation of the number of components in multivariate mixtures.
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- Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2014, v. 76, n. 1, p. 97, doi. 10.1111/rssb.12022
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Ranking scientific journals via latent class models for polytomous item response data.
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- Journal of the Royal Statistical Society: Series A (Statistics in Society), 2015, v. 178, n. 4, p. 1025, doi. 10.1111/rssa.12106
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A Smooth Transition Finite Mixture Model for Accommodating Unobserved Heterogeneity.
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- Journal of Business & Economic Statistics, 2020, v. 38, n. 3, p. 580, doi. 10.1080/07350015.2018.1543126
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Bank Business Models at Zero Interest Rates.
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- Journal of Business & Economic Statistics, 2019, v. 37, n. 3, p. 542, doi. 10.1080/07350015.2017.1386567
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Survival and Reliability Analysis with an Epsilon-Positive Family of Distributions with Applications.
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- Symmetry (20738994), 2021, v. 13, n. 5, p. 908, doi. 10.3390/sym13050908
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Quantile-Based Estimation of the Finite Cauchy Mixture Model.
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- Symmetry (20738994), 2019, v. 11, n. 9, p. 1186, doi. 10.3390/sym11091186
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Bayesian Stable Mixture Model of State Densities of Generalized Chua's Circuit.
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- International Journal of Bifurcation & Chaos in Applied Sciences & Engineering, 2015, v. 25, n. 3, p. -1, doi. 10.1142/S0218127415500388
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Intelligent Recognition of Acoustic and Vibration Threats for Security Breach Detection, Close Proximity Danger Identification, and Perimeter Protection.
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- Homeland Security Affairs, 2011, v. 7, p. 1
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Are all Homeowners Willing to Pay for Better Schools? ─ Evidence from a Finite Mixture Model Approach.
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- Journal of Real Estate Finance & Economics, 2019, v. 58, n. 4, p. 638, doi. 10.1007/s11146-018-9658-z
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Log-cumulants of the finite mixture model and their application to statistical analysis of fully polarimetric UAVSAR data.
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- Geo-Spatial Information Science, 2018, v. 21, n. 1, p. 45, doi. 10.1080/10095020.2017.1419607
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On Fair Person Classification Based on Efficient Factor Score Estimates in the Multidimensional Factor Analysis Model.
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- Psychometrika, 2018, v. 83, n. 3, p. 563, doi. 10.1007/s11336-018-9613-1
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Robust Measurement via A Fused Latent and Graphical Item Response Theory Model.
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- Psychometrika, 2018, v. 83, n. 3, p. 538, doi. 10.1007/s11336-018-9610-4
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Dealing with Reflection Invariance in Bayesian Factor Analysis.
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- Psychometrika, 2017, v. 82, n. 2, p. 295, doi. 10.1007/s11336-017-9564-y
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A Unified Framework for the Comparison of Treatments with Ordinal Responses.
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- Psychometrika, 2014, v. 79, n. 4, p. 605, doi. 10.1007/s11336-013-9367-8
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Bayesian Inferences of Latent Class Models with an Unknown Number of Classes.
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- Psychometrika, 2014, v. 79, n. 4, p. 621, doi. 10.1007/s11336-013-9368-7
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Finite Mixtures of Matrix Variate t Distributions.
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- Gazi University Journal of Science, 2016, v. 29, n. 2, p. 335
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Finite mixture clustering of human tissues with different levels of IGF-1 splice variants mRNA transcripts.
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- BMC Bioinformatics, 2015, v. 16, n. 1, p. 1, doi. 10.1186/s12859-015-0689-7
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ANTECEDENTS OF ONLINE PURCHASE INTENTION AND BEHAVIOUR: UNCOVERING UNOBSERVED HETEROGENEITY.
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- Journal of Business Economics & Management, 2019, v. 20, n. 1, p. 131, doi. 10.3846/jbem.2019.7060
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Long-run Relations between Childhood Shocks and Health in Late Adulthood—Evidence from the Survey of Health, Ageing, and Retirement in Europe.
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- CESifo Economic Studies, 2014, v. 60, n. 2, p. 402, doi. 10.1093/cesifo/ifu015
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How to use statistics to claim antagonism and synergism from binary mixture experiments.
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- Pest Management Science, 2021, v. 77, n. 9, p. 3890, doi. 10.1002/ps.6348
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Bayesian generalizations of the integer-valued autoregressive model.
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- Journal of Applied Statistics, 2022, v. 49, n. 2, p. 336, doi. 10.1080/02664763.2020.1812544
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Nonlinear semiparametric autoregressive model with finite mixtures of scale mixtures of skew normal innovations.
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- Journal of Applied Statistics, 2019, v. 46, n. 11, p. 2010, doi. 10.1080/02664763.2019.1575953
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Variable diagnostics in model-based clustering through variation partition.
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- Journal of Applied Statistics, 2018, v. 45, n. 16, p. 2888, doi. 10.1080/02664763.2018.1444740
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Empirical Bayes estimates of finite mixture of negative binomial regression models and its application to highway safety.
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- Journal of Applied Statistics, 2018, v. 45, n. 9, p. 1652, doi. 10.1080/02664763.2017.1389863
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A Bayesian finite mixture change-point model for assessing the risk of novice teenage drivers.
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- Journal of Applied Statistics, 2018, v. 45, n. 4, p. 604, doi. 10.1080/02664763.2017.1288202
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Joint analysis of nonlinear heterogeneous longitudinal data and binary outcome: an application to AIDS clinical studies.
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- Journal of Applied Statistics, 2016, v. 43, n. 15, p. 2713, doi. 10.1080/02664763.2016.1142951
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A latent variable model for analyzing mixed longitudinal (k,l)-inflated count and ordinal responses.
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- Journal of Applied Statistics, 2016, v. 43, n. 12, p. 2203, doi. 10.1080/02664763.2015.1134448
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Bayesian analysis for mixtures of discrete distributions with a non-parametric component.
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- Journal of Applied Statistics, 2016, v. 43, n. 8, p. 1369, doi. 10.1080/02664763.2015.1100594
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