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1. Mixtures
: estimation and applications
by Mengersen, Kerrie L and Robert, Christian P., 1961 and Titterington, D. M
2011, 1. Aufl., Wiley series in probability and statistics, ISBN 111999845X, xviii, 311
Mixture distributions (Probability theory) | Distribution (Probability theory)
Book
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2. Mixture model-based classification
by McNicholas, Paul D., author
2016, 1, ISBN 1482225662, xxiv, 212 pages
Hierarchical clustering (Cluster analysis) | Discriminant analysis | Multiple comparisons (Statistics) | Classification | Mixture distributions (Probability theory) | Mathematics | Methods | Statistical Theory & Methods | Bioinformatics | Psychological Methods & Statistics
Book
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3. Full Text The subspace Gaussian mixture model—A structured model for speech recognition
by Povey, Daniel and Burget, Lukáš and Agarwal, Mohit and Akyazi, Pinar and Kai, Feng and Ghoshal, Arnab and Glembek, Ondřej and Goel, Nagendra and Karafiát, Martin and Rastrow, Ariya and Rose, Richard C and Schwarz, Petr and Thomas, Samuel
Computer speech & language, ISSN 0885-2308, 2011, Volume 25, Issue 2, pp. 404 - 439
Subspace Gaussian Mixture Model | Gaussian Mixture Model | Speech recognition | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Applied linguistics | Linguistics | Computational linguistics | Voice recognition | Markov processes | Models | Mathematical analysis | C (programming language) | Speech | Gaussian | Mathematical models | Vectors (mathematics) | Standards
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4. Full Text Aerosol-climate interactions in the Norwegian Earth System Model-NorESM1-M
by Kirkevag, A and Iversen, T and Seland, O and Hoose, C and Kristjansson, J. E and Struthers, H and Ekman, A. M. L and Ghan, S and Griesfeller, J and Nilsson, E. D and Schulz, M and Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Geoscientific model development, ISSN 1991-959X, 01/2013, Volume 6, Issue 1, pp. 207 - 244
Geosciences, Multidisciplinary | Physical Sciences | Geology | Science & Technology | Air pollution | Models | Precipitation (Meteorology) | Clouds | Analysis | Dust | Modules | Aerosols | Droplets | Sulfates | Estimates | Radiative forcing | ENVIRONMENTAL SCIENCES | Earth 1 | NorESM | aerosol-climate | Norwegian | interactions
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5. Full Text Finite mixture models
by McLachlan, Geoffrey J., 1946 and Peel, David, 1971
2000, 1. Aufl., Wiley series in probability and statistics. Applied probability and statistics section, ISBN 9780471006268, 450
Mixture distributions (Probability theory) | Probability & Statistics | General | Mathematics
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6. Advanced techniques for modelling maternal and child health in Africa
by Kandala, Ngianga-Bakwin, editor and Ghilagaber, Gebrenegus, editor
2014, The Springer series on demographic methods and population analysis, ISBN 9789400767782, Volume 34, xiv, 330
Child Welfare | Statistics as Topic | Maternal Welfare | Africa | Child Mortality | Child health services | Demography | Maternal and infant welfare | Maternal health services | Children | Mothers | The Demographic and Health Survey | Child health problems | Medical and Health Sciences | Clustering within family and household | Medicin och hälsovetenskap | Public Health, Global Health, Social Medicine and Epidemiology | Hälsovetenskaper | Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi | Modelling childhood mortality | hälso- och sjukvårdsforskning | Vascular diseases in South Africa | Interdependencies over life-course events | Tools for HIV prevention | Geo-additive Baysian discrete-time survival model | Survey data in developing countries | Health Sciences | World Fertility Survey | Baysian structures additive regression | statistik | Prevalent hypertension in Sub-Saharan Africa | Statistics | Semiparametric stratified survival model | Modelling maternal and child health | demografi | Stepwise geoadditive regression model | Flexible spatial mixture models | Modern and advance statistical techniques | Effetcs of health inputs on child survival | Non-random utilization of health services
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7. Full Text The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity
by Denzil G. Fiebig and Michael P. Keane and Jordan Louviere and Nada Wasi
Marketing science (Providence, R.I.), ISSN 0732-2399, 5/2010, Volume 29, Issue 3, pp. 393 - 421
choice experiments | choice models | mixture models | consumer heterogeneity | Datasets | Economic models | Utility models | Cell phones | Credit cards | Modeling | Parametric models | Scale modeling | Pizzas | Marketing | Choice experiments | Consumer heterogeneity | Choice models | Mixture models | Business & Economics | Social Sciences | Business | choice models; mixture models; consumer heterogeneity; choice experiments | Monte Carlo method | Consumer behavior | Usage | Consumer preferences | Logits | Models | Testing | Studies | Market segments | Utility functions | Consumers | Product development
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8. Full Text Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data
by DiRenzo, Graziella V and Che‐Castaldo, Christian and Saunders, Sarah P and Campbell Grant, Evan H and Zipkin, Elise F
Ecology and evolution, ISSN 2045-7758, 01/2019, Volume 9, Issue 2, pp. 899 - 909
occupancy model | generalized N‐mixture model | Bayesian | emerging infectious diseases | host–pathogen interaction | hierarchical models | mark–recapture models | multistate models | disease ecology | Dail–Madsen model | generalized N-mixture model | Environmental Sciences & Ecology | Ecology | Life Sciences & Biomedicine | Evolutionary Biology | Science & Technology | Parameter estimation | Theory | Population number | Animal diseases | Infections | Statistical methods | Probabilistic models | Biodiversity | Reptiles & amphibians | Ecologists | Wildlife | Dynamics | Population | Mathematical models | Arachnids | Pathogens | Statistical analysis | Probability | Birds | Estimates | Disease control | Population (statistical) | Infectious diseases | Disease transmission | State space models | Immigration | Error detection | Wildlife management
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9. Full Text Model-Based Clustering
by McNicholas, Paul D
Journal of classification, ISSN 0176-4268, 10/2016, Volume 33, Issue 3, pp. 331 - 373
Cluster analysis | Pattern Recognition | Signal,Image and Speech Processing | Mixture models | Statistical Theory and Methods | Psychometrics | Cluster | Statistics | Bioinformatics | Marketing | Mathematics, Interdisciplinary Applications | Physical Sciences | Social Sciences | Psychology | Mathematics | Science & Technology | Psychology, Mathematical | Probabilistic models | Clustering | Classification
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