Relevant bibliographies by topics / GLMM

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'GLMM'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "GLMM"

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Tran, M. N., N. Nguyen, D. Nott, and R. Kohn. "Bayesian Deep Net GLM and GLMM." Journal of Computational and Graphical Statistics 29, no. 1 (2019): 97–113. http://dx.doi.org/10.1080/10618600.2019.1637747.

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Garrido, José, and Jun Zhou. "Full Credibility with Generalized Linear and Mixed Models." ASTIN Bulletin 39, no. 1 (2009): 61–80. http://dx.doi.org/10.2143/ast.39.1.2038056.

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AbstractGeneralized linear models (GLMs) are gaining popularity as a statistical analysis method for insurance data. For segmented portfolios, as in car insurance, the question of credibility arises naturally; how many observations are needed in a risk class before the GLM estimators can be considered credible? In this paper we study the limited fluctuations credibility of the GLM estimators as well as in the extended case of generalized linear mixed model (GLMMs). We show how credibility depends on the sample size, the distribution of covariates and the link function. This provides a mechanis
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Glanzmann, Philipp, John Gustafson, Hithoshi Komatsuzawa, Kouji Ohta, and Brigitte Berger-Bächi. "glmM Operon and Methicillin-ResistantglmM Suppressor Mutants in Staphylococcus aureus." Antimicrobial Agents and Chemotherapy 43, no. 2 (1999): 240–45. http://dx.doi.org/10.1128/aac.43.2.240.

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ABSTRACT The Staphylococcus aureus phosphoglucosamine mutase gene glmM was shown to be the last gene of a three-cistron operon, orf1-orf2-glmM. One transcriptional start was identified upstream of orf1, and a second start producing a monocistronic transcript was identified upstream of glmM. Disruption of glmM abolished GlmM production, decreased methicillin resistance, and resulted in teicoplanin hypersusceptibility without affecting the production of the endogenous penicillin-binding proteins and PBP 2′. Complementation of the glmM mutation by the complete glmMoperon restored both methicillin
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MAIORANO, Amanda Marchi, Thiago Santos MOTA, Ana Carolina VERDUGO, et al. "COMPARATIVE STUDY OF CATTLE TICK RESISTANCE USING GENERALIZED LINEAR MIXED MODELS." REVISTA BRASILEIRA DE BIOMETRIA 37, no. 1 (2019): 41. http://dx.doi.org/10.28951/rbb.v37i1.341.

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Comparison of tick resistance in Bos taurus indicus (Nelore) and Bos taurus taurus (Simmental and Caracu) subspecies was investigated utilizing generalized linear mixed models (GLMMs) with Poisson and Negative binomial distributions. Nelore animals (NE) are known to present greater resistance than t. taurus. Difference between tick resistance in Simmental (SI) and Caracu (CA) breeds has never been reported previously. Three artificial tick infestations were conducted to evaluate tick resistance in these breeds. The statistic point of the present study was to show alternative models for the eva
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Park, Hyun-Jeong, Dayeon Lee, and Hyeonju Kwon. "Fitting the GLMM tree to educational data: focusing on differential effects of afterschool program and private tutoring participation." Korean Society for Educational Evaluation 35, no. 4 (2022): 577–607. http://dx.doi.org/10.31158/jeev.2022.35.4.577.

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This study aims to introduce the GLMM tree and show its usefulness in educational research. The GLMM tree model is an extension of MOB to be applied to multilevel data, which detects subgroups with differential effects to estimate the fixed-effect in each subgroup and the random effect by the cluster to which each observation belongs. In this study, we identified the differential effects by detecting subgroups of afterschool programs and private tutoring participation in mathematics achievement of second grade high school students. Using the GLMM trees, students were divided into 16 and 15 sub
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Hayati, Ma'rufah, and Agus Muslim. "Generalized Linear Mixed Model and Lasso Regularization for Statistical Downscaling." Enthusiastic : International Journal of Applied Statistics and Data Science 1, no. 01 (2021): 36–52. http://dx.doi.org/10.20885/enthusiastic.vol1.iss1.art6.

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Rainfall is one of the climatic elements in the tropics which is very influential in agriculture, especially in determining the growing season. Thus, proper rainfall modeling is needed to help determine the best time to start cultivating the soil. Rainfall modeling can be done using the Statistical Downscaling (SDS) method. SDS is a statistical model in the field of climatology to analyze the relationship between large-scale and small-scale climate data. This study uses response variables as a small-scale climate data in the form of rainfall and explanatory variables as a large-scale climate d
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Yan, Zhiyu, Kori S. Zachrison, Lee H. Schwamm, Juan J. Estrada, and Rui Duan. "A privacy-preserving and computation-efficient federated algorithm for generalized linear mixed models to analyze correlated electronic health records data." PLOS ONE 18, no. 1 (2023): e0280192. http://dx.doi.org/10.1371/journal.pone.0280192.

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Large collaborative research networks provide opportunities to jointly analyze multicenter electronic health record (EHR) data, which can improve the sample size, diversity of the study population, and generalizability of the results. However, there are challenges to analyzing multicenter EHR data including privacy protection, large-scale computation resource requirements, heterogeneity across sites, and correlated observations. In this paper, we propose a federated algorithm for generalized linear mixed models (Fed-GLMM), which can flexibly model multicenter longitudinal or correlated data wh
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Setiawan, Erwan, Khairil Anwar Notodiputro, and Bagus Sartono. "Generalized Linear Mixed-Model Tree for Modeling Dengue Fever Cases." CogITo Smart Journal 10, no. 2 (2024): 380–92. https://doi.org/10.31154/cogito.v10i2.715.380-392.

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The GLMM tree demonstrates flexibility when applied to complex dataset structures such as multilevel and longitudinal data. However, there has been no assessment of the performance of GLMM trees on panel data structures. This study aims to assess the performance of the GLMM tree on a panel data structure using a case study of dengue fever cases in West Java. The performance evaluation focuses on the accuracy of the model. The dataset includes cross-sectional data from 27 regencies/cities in West Jawa, covering different regions at a single point in time, and time-series data from 2014 to 2022,
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Pasomboon, Pailin, Pramote Chumnanpuen, and Teerasak E-kobon. "Comparison of Hyaluronic Acid Biosynthetic Genes From Different Strains of Pasteurella multocida." Bioinformatics and Biology Insights 15 (January 2021): 117793222110274. http://dx.doi.org/10.1177/11779322211027406.

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Pasteurella multocida produces a capsule composed of different polysaccharides according to the capsular serotype (A, B, D, E, and F). Hyaluronic acid (HA) is a component of certain capsular types of this bacterium, especially capsular type A. Previously, 2 HA biosynthetic genes from a capsular type A strain were studied for the industrial-scale improvement of HA production. Molecular comparison of these genes across different capsular serotypes of P multocida has not been reported. This study aimed to compare 8 HA biosynthetic genes ( pgi, pgm, galU, hyaC, glmS, glmM, glmU, and hyaD) of 22 P
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Nurfadilah, Khalilah, Asfar, Khairil A. Notodiputro, Bagus Sartono, and Azlam Nas. "Premarital Sex Behavior Model with Generalized Linear Mixed Model Least Absolute Shrinkage and Selection Operator dan Generalized Linear Mixed Model GROUP Least Absolute Shrinkage and Selection Operator." STATISTIKA Journal of Theoretical Statistics and Its Applications 23, no. 1 (2023): 48–56. http://dx.doi.org/10.29313/statistika.v23i1.1953.

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 Premarital sexual behavior is sexual behavior that is carried out between men and women without legal marriage. As the number of premarital sex increases, efforts need to take. One that can do is to identify the main factors contributing to reducing or increasing premarital sex behavior by a Regression model. In the context of sexual behavior, environmental influences cannot be ignored. GLMM is used to model data that is grouped into certain Groups, include environment effect that is modeled as mixed effect in GLMM. In terms of parsimony, the LASSO method can do selection variab
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Dissertations / Theses on the topic "GLMM"

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Zhang, Hongbin. "Joint inference of NLME and GLMM models with informative censoring." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/51124.

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Non-linear mixed effects models (NLME) and generalized linear mixed effects models (GLMM) are commonly used to model longitudinal process. This thesis goes beyond the single process modelling and focuses on jointly modelling multiple longitudinal processes with different types of variables. In particular, we investigate methods on joint inference of NLME and GLMM models for the following three problems: (1) joint models of NLME and GLMM for complete data with NLME for the time-dependent mis-measured covariate and GLMM for discrete longitudinal response; (2) joint models with covariate subject
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Chang, Sheng-Mao. "A Stationary Stochastic Approximation Algorithm for Estimation in the GLMM." NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-05172007-164438/unrestricted/etd.pdf.

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JOLLY, LAURE. "Etude de glmm, phosphoglucosamine mutase impliquee dans la biosynthese du peptidoglycane." Paris 11, 1999. http://www.theses.fr/1999PA112202.

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La phosphoglucosamine mutase, (glmm) de e. Coli, permettant la conversion de la glucosamine-6-phosphate en glucosamine-1-phosphate (etape essentielle de la voie de biosynthese du peptidoglycane et des lipopolysaccharides) a ete purifiee jusqu'a homogeneite et ses proprietes enzymatiques ont ete etudiees. L'enzyme est active sous une forme phosphorylee et catalyse la reaction selon un mecanisme de type ping-pong bi-bi. Les formes phosphorylee et dephosphorylee ont pu etre separees par clhp et un couplage sm a montre qu'un seul phosphate etait lie covalemment a l'enzyme. Le site de phosphorylati
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Nhapi, Raymond T. "A GLMM analysis of data from the Sinovuyo Caring Families Program (SCFP)." Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29507.

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We present an analysis of the data from a longitudinal randomized control trial that assesses the impact of an intervention program aimed at improving the quality of childcare within families. The SCFP was a group-based program implemented over two separate waves conducted in Khayelitsha and Nyanga. The data were collected at baseline, post-test and at one-year follow-up via questionnaires (self-assessment) and observational video coding. Multiple imputation (using chained equations) procedures were used to impute missing information. Generalized linear Mixed Effect Models (GLMMs) were used to
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Chauvet, Jocelyn. "Introducing complex dependency structures into supervised components-based models." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTS008/document.

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Une forte redondance des variables explicatives cause de gros problèmes d'identifiabilité et d'instabilité des coefficients dans les modèles de régression. Même lorsque l'estimation est possible, l'interprétation des résultats est donc extrêmement délicate. Il est alors indispensable de combiner à leur vraisemblance un critère supplémentaire qui régularise l'estimateur. Dans le sillage de la régression PLS, la stratégie de régularisation que nous considérons dans cette thèse est fondée sur l'extraction de composantes supervisées. Contraintes à l'orthogonalité entre elles, ces composantes doive
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Garcia, Diogo Anast?cio. "Avalia??o gen?tica da prenhez precoce em animais da ra?a Nelore utilizando modelos lineares generalizados mistos." UFVJM, 2010. http://acervo.ufvjm.edu.br:8080/jspui/handle/1/730.

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?rea de concentra??o: Produ??o Animal.<br>Submitted by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2015-11-16T13:54:40Z No. of bitstreams: 2 license_rdf: 23898 bytes, checksum: e363e809996cf46ada20da1accfcd9c7 (MD5) diogo_anastacio_garcia.pdf: 241254 bytes, checksum: 3f5025c7cbe992519b20507c5901711c (MD5)<br>Approved for entry into archive by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2015-11-16T13:55:28Z (GMT) No. of bitstreams: 2 license_rdf: 23898 bytes, checksum: e363e809996cf46ada20da1accfcd9c7 (MD5) diogo_anastacio_garcia.pdf: 241254 bytes, checksum: 3f5025c7cbe9925
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Warren, Andrew Mark. "The impact of river flow on the distribution and abundance of salmonid fishes." Thesis, University of St Andrews, 2017. http://hdl.handle.net/10023/11569.

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River flow regime is fundamental in determining lotic fish communities and populations, and especially of salmonid fishes. Quantifying the effects of human induced flow alteration on salmonids is a key question for conservation and water resources management. While qualitative responses to flow alteration are well characterised, a more intractable problem is quantifying responses in a way that is practical for environmental management. Using data drawn from the Environment Agency national database, I fitted generalised linear mixed models (GLMMs) using Bayesian inference to quantify the respon
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Wu, Hongqian. "Proportional likelihood ratio mixed model for longitudinal discrete data." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2296.

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A semiparametric proportional likelihood ratio model was proposed by Luo and Tsai (2012) which is suitable for modeling a nonlinear monotonic relationship between the response variable and a covariate. Extending the generalized linear model, this model leaves the probability distribution unspecified but estimates it from the data. In this thesis, we propose to extend this model into analyzing the longitudinal data by incorporating random effects into the linear predictor. By using this model as the conditional density of the response variable given the random effects, we present a maximum like
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Gray, Emma L. "Ecology and status of a new species of carnivorous marsupial, the Black-Tailed Dusky Antechinus (A. Arktos) and its relationship with a sympatric congener, the Brown Antechinus (A. Stuartii)." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/112503/1/Emma_Gray_Thesis.pdf.

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Since 2012, the number of described species in the carnivorous marsupial genus Antechinus has increased by 50%. The present thesis aimed to collect and analyse fundamental ecological data for one newly described species, the black-tailed dusky antechinus, Antechinus arktos, about which virtually nothing was known. Population ecology and geographic range of the species was used to determine conservation status. The foundational ecological information detailed in this thesis concerning breeding biology, diet, activity patterns and optimal detection methods, will assist in planning future conserv
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Eufrázio, Sofia Raquel Lavado. "Avaliação do efeito barreira das estradas na abundância e uso do espaço do rato-do-campo (Apodemus sylvaticus)." Master's thesis, Universidade de Évora, 2010. http://hdl.handle.net/10174/20841.

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As estradas são essenciais ao desenvolvimento da economia, mas também um dos maiores problemas de conservação. Porém, os seus efeitos nas populações de micromamíferos são controversos. Este estudo pretendeu quantificar o efeito da estrada nos parâmetros populacionais e no padrão espacial do rato-do-campo (Apodemus sylvaticus) incluindo os efeitos do microhabitat. Uma área de montado atravessada por uma estrada e outra sem o efeito de estrada (controlo) foram comparadas no sul de Portugal. Os parâmetros populacionais avaliaram-se pelo modelo robusto de Pollock. O efeito do microhabitat no uso d
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Books on the topic "GLMM"

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Andreß, Hans-Jürgen. GLIM. Vieweg+Teubner Verlag, 1986. http://dx.doi.org/10.1007/978-3-322-85654-8.

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Pomiankowski, Nick. GLIM - 3. Portsmouth Polytechnic, School of Information Science, 1986.

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5, Wu Ming. Havana glam: Romanzo. Fanucci, 2001.

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Dennis, Di Laura, ed. Barbie glam & glitz. Golden Books, 2007.

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Man-Kong, Mary. Barbie glam & glitz. Golden Books, 2007.

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Kiøsterud, Erland. Fort glem videre: Minnetapet. Aschehoug, 1995.

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1944-, Danielsson Ulla, ed. Glöm inte att låsa. Lind & Co, 2013.

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(Singapore), Urban Redevelopment Authority. Kampong Glam: Historic district. Urban Redevelopment Authority, 1995.

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Coleman, Rosalind. An introduction to GLIM. University of Sheffield, Computing Services, 1987.

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A, Aitkin Murray, ed. Statistical modelling in GLIM. Clarendon Press, 1989.

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Book chapters on the topic "GLMM"

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Stroup, Walter W., Marina Ptukhina, and Julie Garai. "GLMM Estimation." In Generalized Linear Mixed Models, 2nd ed. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9780429092060-7.

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Zuur, Alain F., Elena N. Ieno, Neil J. Walker, Anatoly A. Saveliev, and Graham M. Smith. "GLMM and GAMM." In Statistics for Biology and Health. Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-87458-6_13.

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Stroup, Walter W., Marina Ptukhina, and Julie Garai. "Five Bayesian GLMM Examples." In Generalized Linear Mixed Models, 2nd ed. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9780429092060-23.

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Stroup, Walter W., Marina Ptukhina, and Julie Garai. "Bayesian Implementation of GLMM." In Generalized Linear Mixed Models, 2nd ed. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9780429092060-22.

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Stroup, Walter W., Marina Ptukhina, and Julie Garai. "Pre-GLMM Estimation and Inference Basics." In Generalized Linear Mixed Models, 2nd ed. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9780429092060-6.

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Zhang, Liying, and Laurence Klotz. "Interpreting PSA Kinetics Using GLMM Technique." In Active Surveillance for Localized Prostate Cancer. Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-912-9_11.

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Walker, N. J., A. F. Zuur, A. Ward, A. A. Saveliev, E. N. Ieno, and G. M. Smith. "A Comparison of GLM, GEE, and GLMM Applied to Badger Activity Data." In Statistics for Biology and Health. Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-87458-6_22.

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Salinas Ruíz, Josafhat, Osval Antonio Montesinos López, Gabriela Hernández Ramírez, and Jose Crossa Hiriart. "Objectives of Inference for Stochastic Models." In Generalized Linear Mixed Models with Applications in Agriculture and Biology. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32800-8_3.

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AbstractThroughout this book, we have been using the pseudonym GLMMs to denote generalized linear mixed models. The common denominator among all these models is that they all contain a linear model (LM) part, which refers to the fixed effects component of the linear predictor Xβ. In a GLMM, the prefix “G” indicates that the distribution of observations may not be normal, the suffix of the first M means that the linear predictor includes mixed effects and thus contains random effects, which are expressed by the term “Zb.” The fixed linear component of the predictor Xβ is important because the f
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Crainiceanu, Ciprian M., David Ruppert, Jery R. Stedinger, and Christopher T. Behr. "Improving MCMC Mixing for a GLMM Describing Pathogen Concentrations in Water Supplies." In Case Studies in Bayesian Statistics. Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4612-2078-7_9.

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Rhodes, J. R., C. A. McAlpine, A. F. Zuur, G. M. Smith, and E. N. Ieno. "GLMM Applied on the Spatial Distribution of Koalas in a Fragmented Landscape." In Statistics for Biology and Health. Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-87458-6_21.

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Conference papers on the topic "GLMM"

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Nakajima, Akira, and Hiroyuki Kobayashi. "Semantic Segmentation with GLCM Images." In 21st International Conference on Informatics in Control, Automation and Robotics. SCITEPRESS - Science and Technology Publications, 2024. http://dx.doi.org/10.5220/0013072200003822.

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Rasheed, Hanoona, Muhammad Maaz, Sahal Shaji, et al. "GLaMM: Pixel Grounding Large Multimodal Model." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.01236.

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Gao, Zixin, Yongan Zhang, Pei Liu, Ruijin Fu, and Bing Zhang. "Auto-Focusing in Off-axis Digital Holography Using Gray Level Co-Occurrence Matrix." In Frontiers in Optics. Optica Publishing Group, 2024. https://doi.org/10.1364/fio.2024.jd4a.88.

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We propose employing the gray level co-occurrence matrix (GLCM) to compute the contrast characteristics of holographic reconstructions for auto-focusing. Simulation results demonstrate that this method represents an effective approach for off-axis digital holographic auto-focusing.
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Gillis, David, Emmett Ientilucci, and Jeffrey Bowles. "Results of GLMM-based target detection on the RIT data set." In SPIE Defense, Security, and Sensing, edited by Sylvia S. Shen and Paul E. Lewis. SPIE, 2010. http://dx.doi.org/10.1117/12.850242.

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Luo, Wen. "Establishing Domain-Specific Empirical Benchmarks for GLMM-Based Effect Sizes in SCEDs (Poster 8)." In AERA 2024. AERA, 2024. http://dx.doi.org/10.3102/ip.24.2104299.

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Luo, Wen. "Establishing Domain-Specific Empirical Benchmarks for GLMM-Based Effect Sizes in SCEDs (Poster 8)." In 2024 AERA Annual Meeting. AERA, 2024. http://dx.doi.org/10.3102/2104299.

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Bono, Roser, María J. Blanca, Rafael Alarcón, and Jaume Arnau. "THE EFFECTS OF AUTOCORRELATION AND NUMBER OF REPEATED MEASURES ON GLMM ROBUSTNESS WITH ORDINAL DATA." In 43rd International Academic Conference, Lisbon. International Institute of Social and Economic Sciences, 2018. http://dx.doi.org/10.20472/iac.2018.043.005.

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Handayani, Dian, Khairil Anwar Notodiputro, Kusman Sadik, and Anang Kurnia. "A comparative study of approximation methods for maximum likelihood estimation in generalized linear mixed models (GLMM)." In STATISTICS AND ITS APPLICATIONS: Proceedings of the 2nd International Conference on Applied Statistics (ICAS II), 2016. Author(s), 2017. http://dx.doi.org/10.1063/1.4979449.

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Romanov, M. S., and V. B. Masterov. "Analysis of Steller's Sea Eagle reproduction efficiency on Sakhalin Island using Generalized Linear Mixed Models (GLMM)." In Mathematical Biology and Bioinformatics. IMPB RAS - Branch of KIAM RAS, 2022. http://dx.doi.org/10.17537/icmbb22.47.

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Sihombing, Pardomuan Robinson, Khairil A. Notodiputro, and Bagus Sartono. "Comparison of GEE and GLMM methods for longitudinal data (Case study: Determinants of the percentage of poor people in Indonesia, 2015-2019)." In THE 2ND UNIVERSITAS LAMPUNG INTERNATIONAL CONFERENCE ON SCIENCE, TECHNOLOGY, AND ENVIRONMENT (ULICoSTE) 2021. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0103254.

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Reports on the topic "GLMM"

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Karimi, Omid, Fatemeh Hosseini, and Mohsen Mohammadzadeh. Pairwise Likelihood in Spatial GLMM with Skew Normal Latent Variables. Cogeo@oeaw-giscience, 2011. http://dx.doi.org/10.5242/iamg.2011.0246.

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Burdett, Samantha. Zipped and Glam. Iowa State University, Digital Repository, 2014. http://dx.doi.org/10.31274/itaa_proceedings-180814-1020.

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Moral, Rafael. Introduction to Generalized Linear Models. Instats Inc., 2024. http://dx.doi.org/10.61700/vteee3zjf6fsm1478.

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This seminar provides a comprehensive introduction to Generalized Linear Models (GLMs), covering binary, binomial, categorical logistic regression, Poisson regression, and advanced topics like overdispersion and zero-inflated models. Participants will gain theoretical knowledge and practical skills in applying GLMs using R, enhancing their ability to perform rigorous statistical analyses in various research scenarios.
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Armstrong, Dave. Generalized Linear Models for Social and Health Sciences. Instats Inc., 2023. http://dx.doi.org/10.61700/dpngncc99f4pr469.

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This 12-week workshop provides a comprehensive understanding of GLMs and their application in various social and health science disciplines. With a lecture overview and hands-on lab component for each week, participants will gain practical experience in using R for implementing GLMs, evaluating model fit and presenting model results. An official Instats certificate of completion and 3 ECTS Equivalent points are provided at the conclusion of the seminar.
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Peterson, Michael Jay. Overview of Physics-Based GLM Level-3 Products. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1578011.

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Federer, W. T., Z. D. Feng, M. P. Meredith, and N. J. Miles-McDermott. Annotated Computer Output for Split Plot Design: SAS GLM. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada190800.

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Anantharajan, Shenbagarajan, and Shenbagalakshmi Gunasekaran. Detection and Classification of MRI Brain Tumour Using GLCM and Enhanced K-NN. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2021. http://dx.doi.org/10.7546/crabs.2021.02.13.

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Huo, Zhenyu, Feifei Chong, Lingyu Yin, Zongliang Lu, Jie Liu, and Hongxia Xu. Accuracy of the GLIM criteria for diagnosing malnutrition: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.2.0061.

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Yin, Liangyu, Feifei Chong, Zhenyu Huo, Na Li, Jie Liu, and Hongxia Xu. GLIM-defined malnutrition and overall survival in cancer patients: A systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.7.0113.

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Hengsdijk, Huib, Thierry Stokkermans, and Abel van Hoeven. Evaluatie van goede landbouw- en milieucondities 5 (GLMC-5) : GLB maatregelen voor bodembewerkingsbeheer in Zuid Limburg. Wageningen Plant Research, 2024. http://dx.doi.org/10.18174/644294.

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