Relevant bibliographies by topics / Generalized Linear Modelling

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

Academic literature on the topic 'Generalized Linear Modelling'

Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Generalized Linear Modelling"

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Wilson, K., and B. T. Grenfell. "Generalized linear modelling for parasitologists." Parasitology Today 13, no. 1 (January 1997): 33–38. http://dx.doi.org/10.1016/s0169-4758(96)40009-6.

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Atkinson, Peter, Hester Jiskoot, Remo Massari, and Tavi Murray. "Generalized linear modelling in geomorphology." Earth Surface Processes and Landforms 23, no. 13 (December 1998): 1185–95. http://dx.doi.org/10.1002/(sici)1096-9837(199812)23:13<1185::aid-esp928>3.0.co;2-w.

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Schuenemeyer, John H., P. McCullagh, and J. A. Nelder. "Generalized Linear Models." Technometrics 34, no. 2 (May 1992): 224. http://dx.doi.org/10.2307/1269238.

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Breslow, Norman, Ludwig Fahrmeir, and Gerhard Tutz. "Multivariate Statistical Modelling Based on Generalized Linear Models." Journal of the American Statistical Association 91, no. 434 (June 1996): 908. http://dx.doi.org/10.2307/2291687.

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Glosup, Jeffrey. "Multivariate Statistical Modelling Based on Generalized Linear Models." Technometrics 37, no. 3 (August 1995): 350–51. http://dx.doi.org/10.1080/00401706.1995.10484351.

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Chappell, Rick. "Multivariate Statistical Modelling Based on Generalized Linear Models." Journal of the American Statistical Association 98, no. 463 (September 2003): 776–77. http://dx.doi.org/10.1198/jasa.2003.s302.

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Ziegel, Eric. "Multivariate Statistical Modelling Based on Generalized Linear Models." Technometrics 44, no. 1 (February 2002): 94. http://dx.doi.org/10.1198/tech.2002.s673.

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LEE, JAMES, H. P. LEE, and K. S. CHIA. "Analysis of Registry Data by Generalized Linear Modelling." International Journal of Epidemiology 19, no. 2 (1990): 472–73. http://dx.doi.org/10.1093/ije/19.2.472.

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Sutton, G. R., and B. J. Moore. "Velocity modelling using a generalized linear inversion technique." Exploration Geophysics 16, no. 2-3 (June 1985): 287–88. http://dx.doi.org/10.1071/eg985287.

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Yunus, Rossita M., Masud M. Hasan, Nuradhiathy A. Razak, Yong Z. Zubairi, and Peter K. Dunn. "Modelling daily rainfall with climatological predictors: Poisson-gamma generalized linear modelling approach." International Journal of Climatology 37, no. 3 (June 10, 2016): 1391–99. http://dx.doi.org/10.1002/joc.4784.

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Dissertations / Theses on the topic "Generalized Linear Modelling"

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Schnatter, Sylvia. "Integration-based Kalman-filtering for a Dynamic Generalized Linear Trend Model." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1991. http://epub.wu.ac.at/424/1/document.pdf.

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The topic of the paper is filtering for non-Gaussian dynamic (state space) models by approximate computation of posterior moments using numerical integration. A Gauss-Hermite procedure is implemented based on the approximate posterior mode estimator and curvature recently proposed in 121. This integration-based filtering method will be illustrated by a dynamic trend model for non-Gaussian time series. Comparision of the proposed method with other approximations ([15], [2]) is carried out by simulation experiments for time series from Poisson, exponential and Gamma distributions. (author's abstract)
Series: Forschungsberichte / Institut für Statistik
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Nargis, Suraiya, and n/a. "Robust methods in logistic regression." University of Canberra. Information Sciences & Engineering, 2005. http://erl.canberra.edu.au./public/adt-AUC20051111.141200.

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My Masters research aims to deepen our understanding of the behaviour of robust methods in logistic regression. Logistic regression is a special case of Generalized Linear Modelling (GLM), which is a powerful and popular technique for modelling a large variety of data. Robust methods are useful in reducing the effect of outlying values in the response variable on parameter estimates. A literature survey shows that we are still at the beginning of being able to detect extreme observations in logistic regression analyses, to apply robust methods in logistic regression and to present informatively the results of logistic regression analyses. In Chapter 1 I have made a basic introduction to logistic regression, with an example, and to robust methods in general. In Chapters 2 through 4 of the thesis I have described traditional methods and some relatively new methods for presenting results of logistic regression using powerful visualization techniques as well as the concepts of outliers in binomial data. I have used different published data sets for illustration, such as the Prostate Cancer data set, the Damaged Carrots data set and the Recumbent Cow data set. In Chapter 4 I summarize and report on the modem concepts of graphical methods, such as central dimension reduction, and the use of graphics as pioneered by Cook and Weisberg (1999). In Section 4.6 I have then extended the work of Cook and Weisberg to robust logistic regression. In Chapter 5 I have described simulation studies to investigate the effects of outlying observations on logistic regression (robust and non-robust). In Section 5.2 I have come to the conclusion that, in the case of classical or robust multiple logistic regression with no outliers, robust methods do not necessarily provide more reasonable estimates of the parameters for the data that contain no st~ong outliers. In Section 5.4 I have looked into the cases where outliers are present and have come to the conclusion that either the breakdown method or a sensitivity analysis provides reasonable parameter estimates in that situation. Finally, I have identified areas for further study.
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Mallya, Shruti. "Modelling Human Risk of West Nile Virus Using Surveillance and Environmental Data." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/35734.

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Limited research has been performed in Ontario to ascertain risk factors for West Nile Virus (WNV) and to develop a unified risk prediction strategy. The aim of the current body of work was to use spatio-temporal modelling in conjunction with surveillance and environmental data to determine which pre-WNV season factors could forecast a high risk season and to explore how well mosquito surveillance data could predict human cases in space and time during the WNV season. Generalized linear mixed modelling found that mean minimum monthly temperature variables and annual WNV-positive mosquito pools were most significantly predictive of number of human WNV cases (p<0.001). Spatio-temporal cluster analysis found that positive mosquito pool clusters could predict human case clusters up to one month in advance. These results demonstrate the usefulness of mosquito surveillance data as well as publicly available climate data for assessing risk and informing public health practice.
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Charalambous, Christiana. "Variable selection in joint modelling of mean and variance for multilevel data." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/variable-selection-in-joint-modelling-of-mean-and-variance-for-multilevel-data(cbe5eb08-1e77-4b44-b7df-17bd4bf4937f).html.

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We propose to extend the use of penalized likelihood based variable selection methods to hierarchical generalized linear models (HGLMs) for jointly modellingboth the mean and variance structures. We are interested in applying these newmethods on multilevel structured data, hence we assume a two-level hierarchical structure, with subjects nested within groups. We consider a generalized linearmixed model (GLMM) for the mean, with a structured dispersion in the formof a generalized linear model (GLM). In the first instance, we model the varianceof the random effects which are present in the mean model, or in otherwords the variation between groups (between-level variation). In the second scenario,we model the dispersion parameter associated with the conditional varianceof the response, which could also be thought of as the variation betweensubjects (within-level variation). To do variable selection, we use the smoothlyclipped absolute deviation (SCAD) penalty, a penalized likelihood variable selectionmethod, which shrinks the coefficients of redundant variables to 0 and at thesame time estimates the coefficients of the remaining important covariates. Ourmethods are likelihood based and so in order to estimate the fixed effects in ourmodels, we apply iterative procedures such as the Newton-Raphson method, inthe form of the LQA algorithm proposed by Fan and Li (2001). We carry out simulationstudies for both the joint models for the mean and variance of the randomeffects, as well as the joint models for the mean and dispersion of the response,to assess the performance of our new procedures against a similar process whichexcludes variable selection. The results show that our method increases both theaccuracy and efficiency of the resulting penalized MLEs and has 100% successrate in identifying the zero and non-zero components over 100 simulations. Forthe main real data analysis, we use the Health Survey for England (HSE) 2004dataset. We investigate how obesity is linked to several factors such as smoking,drinking, exercise, long-standing illness, to name a few. We also discover whetherthere is variation in obesity between individuals and between households of individuals,as well as test whether that variation depends on some of the factorsaffecting obesity itself.
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Carreira, Inês Duarte. "Modelling dependence between frequency and severity of insurance claims." Master's thesis, Instituto Superior de Economia e Gestão, 2017. http://hdl.handle.net/10400.5/14631.

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Mestrado em Actuarial Science
A estimação da perda individual é uma importante tarefa para calcular os preços das apólices de seguro. A abordagem padrão assume independência entre a frequência e a severidade dos sinistros, o que pode não ser uma suposição realística. Neste texto, a dependência entre números e montantes de sinistros é explorada, num contexto de Modelos Lineares Generalizados. Um modelo de severidade condicional e um modelo de Cópula são apresentados como alternativas para modelar esta dependência e posteriormente aplicados a um conjunto de dados fornecido por uma seguradora portuguesa. No final, a comparação com o cenário de independência é realizada.
The estimation of the individual loss is an important task to price insurance policies. The standard approach assumes independence between claim frequency and severity, which may not be a realistic assumption. In this text, the dependence between claim counts and claim sizes is explored, in a Generalized Linear Model framework. A Conditional severity model and a Copula model are presented as alternatives to model this dependence and later applied to a data set provided by a Portuguese insurance company. At the end, the comparison with the independence scenario is carried out.
info:eu-repo/semantics/publishedVersion
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Creegan, Helen P. "Modelling the effects of changing habitat characteristics and spatial pattern on woodland songbird distributions in West and Central Scotland." Thesis, University of Stirling, 2005. http://hdl.handle.net/1893/48.

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This study investigated bird distributions in relation to local habitat and landscape pattern and the implications which habitat fragmentation may have for woodland birds. There were two sections to the research: an experimental study investigating bird gap crossing behaviour across distances of five to 120m; and an observational study modelling woodland bird distributions in relation to local habitat and landscape scale variables in two study areas (East Loch Lomond and the Central Scotland Forest). In the experimental study it was hypothesised that bird willingness to cross gaps will decrease with increasing gap distance even at home-range scales and that the rate of decline will vary interspecifically in relation to bird morphology. Song thrush mobbing calls played at woodland edges in the West of Scotland were used to attract birds across gaps and results were compared with the response along woodland edges. Data were obtained for four species: chaffinch, coal tit, robin and goldcrest. The decline in response with distance across gaps and along woodland edge was modelled for each species using generalized linear modelling. Maximum gap crossing distances ranged from 46m (goldcrest) to 150m (extrapolated value for the chaffinch). Goldcrests responded more readily through woodlands. There was no difference between woodland edge and gap response for the coal tit. Robins and chaffinches however responded more readily across gaps than through woodland. When different response indices were plotted against bird mass and wing area, results suggested that larger birds with bigger wings responded more readily across gaps than through woodland. It is suggested that this relates to differences in bird manoeuvrability within woodlands and ability to evade a predator in gaps. Fragmentation indices were calculated for an area of the Central Scotland Forest to show how willingness to cross different gap distances influences perception of how fragmented the woodlands are in a region. Results are discussed in the context of the creation of Forest Habitat Networks. The data for the observational section of the work was from bird point counts for 200 sample points at East Loch Lomond in 1998 and 2000 and 267 sample points in the Central Scotland Forest in 1999. In addition a time series of point count data was available for 30 sample points at East Loch Lomond. Additional data was gathered for ten sample points (1998) and two sample points (2000) at East Loch Lomond to investigate effects of observer, time and weather on count data. Generalized linear and generalized additive modelling was carried out on these additional data. Results indicated that biases due to the variation in time and weather conditions between counts existed in the pure count data but that these were eliminated by reducing data to presence and absence form for analysis. Species accumulation curves indicated that two counts per sample point were insufficient to determine species richness. However a sufficiently large proportion of the species was being detected consistently in two counts of ten minutes duration for it to be valid to model them in relation to habitat and landscape variables. Point count data for East Loch Lomond in 1998 (ELL98) and the Central Scotland Forest in 1999 (CSF99) for the wren, treecreeper, garden warbler, robin, blue tit, blackbird, willow warbler, coal tit, goldcrest, great tit, and song thrush were analysed using generalized additive modelling. In addition models were built for the blackcap (CSF99) and the siskin, redstart and wood warbler (ELL98). Where all relationships were identified as linear, models were rebuilt as GLMs. Models were evaluated using the Area Under the Curve (AUC) of Receiver Operating Characteristic (ROC) plots. AUC values ranged from 0.84-0.99 for ELL98 and from 0.76-0.93 for CSF99 indicating high predictive accuracy. Habitat variables accounted for the largest proportion of explained variation in all models and could be interpreted in terms of bird nesting and feeding behaviour. However additional variation was explained by landscape scale and fragmentation related (especially edge) variables. ELL98 models were used to predict bird distributions for Loch Lomond in 2000 (ELL00) and for the CSF99. Likewise the CSF99 models were used to predict distributions for ELL98 and ELL00. Predicted distributions had useful application in many cases within the ELL site between years. Fewer cases of useful application arose for predicting distributions between sites. Results are discussed in the context of the generality of bird environment relationships and reasons for low predictive accuracy when models are applied between sites and years. Models which had useful application for ELL00 were used to predict bird distributions for 2025 and 2050 at East Loch Lomond. Habitat and landscape changes were projected based on the proposed management for the site. Since woodland regeneration rates are difficult to predict, two scenarios were modelled, one assuming a modest amount of regeneration and one assuming no regeneration. Predictions derived from the ELL98 models showed broad-leaved species increasing in distribution while coniferous species declined. This was in keeping with the expected changes in the relative extent of broad-leaved and coniferous habitat. However, predictions from the CSF99 models were often less readily explicable. The value of the modelling approach is discussed and suggestions are made for further study to improve confidence in the predictions.
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Hardin, Patrik, and Sam Tabari. "Modelling Non-life Insurance Policyholder Price Sensitivity : A Statistical Analysis Performed with Logistic Regression." Thesis, KTH, Matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-209773.

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This bachelor thesis within mathematical statistics studies the possibility of modelling the renewal probability for commercial non-life insurance policyholders. The project was carried out in collaboration with the non-life insurance company If P&C Insurance Ltd. at their headquarters in Stockholm, Sweden. The paper includes an introduction to underlying concepts within insurance and mathematics and a detailed review of the analytical process followed by a discussion and conclusions. The first stages of the project were the initial collection and processing of explanatory insurance data and the development of a logistic regression model for policy renewal. An initial model was built and modern methods of mathematics and statistics were applied in order obtain a final model consisting of 9 significant characteristics. The regression model had a predictive power of 61%. This suggests that it to a certain degree is possible to predict the renewal probability of non-life insurance policyholders based on their characteristics. The results from the final model were ultimately translated into a measure of price sensitivity which can be implemented in both pricing models and CRM systems. We believe that price sensitivity analysis, if done correctly, is a natural step in improving the current pricing models in the insurance industry and this project provides a foundation for further research in this area.
Detta kandidatexamensarbete inom matematisk statistik undersöker möjligheten att modellera förnyelsegraden för kommersiella skadeförsärkringskunder. Arbetet utfördes i samarbete med If Skadeförsäkring vid huvudkontoret i Stockholm, Sverige. Uppsatsen innehåller en introduktion till underliggande koncept inom försäkring och matematik samt en utförlig översikt över projektets analytiska process, följt av en diskussion och slutsatser. De huvudsakliga delarna av projektet var insamling och bearbetning av förklarande försäkringsdata samt utvecklandet och tolkningen av en logistisk regressionsmodell för förnyelsegrad. En första modell byggdes och moderna metoder inom matematik och statistik utfördes för att erhålla en slutgiltig regressionsmodell uppbyggd av 9  signifikanta kundkaraktäristika. Regressionsmodellen hade en förklaringsgrad av 61% vilket pekar på att det till en viss grad är möjligt att förklara förnyelsegraden hos försäkringskunder utifrån dessa karaktäristika. Resultaten från den slutgiltiga modellen översattes slutligen till ett priskänslighetsmått vilket möjliggjorde implementering i prissättningsmodeller samt CRM-system. Vi anser att priskänslighetsanalys, om korrekt genomfört, är ett naturligt steg i utvecklingen av dagens prissättningsmodeller inom försäkringsbranschen och detta projekt lägger en grund för fortsatta studier inom detta område.
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Frühwirth-Schnatter, Sylvia. "Applied State Space Modelling of Non-Gaussian Time Series using Integration-based Kalman-filtering." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1993. http://epub.wu.ac.at/1558/1/document.pdf.

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The main topic of the paper is on-line filtering for non-Gaussian dynamic (state space) models by approximate computation of the first two posterior moments using efficient numerical integration. Based on approximating the prior of the state vector by a normal density, we prove that the posterior moments of the state vector are related to the posterior moments of the linear predictor in a simple way. For the linear predictor Gauss-Hermite integration is carried out with automatic reparametrization based on an approximate posterior mode filter. We illustrate how further topics in applied state space modelling such as estimating hyperparameters, computing model likelihoods and predictive residuals, are managed by integration-based Kalman-filtering. The methodology derived in the paper is applied to on-line monitoring of ecological time series and filtering for small count data. (author's abstract)
Series: Forschungsberichte / Institut für Statistik
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Aarts, Geert. "Modelling space-use and habitat preference from wildlife telemetry data." Thesis, St Andrews, 2007. http://hdl.handle.net/10023/327.

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Stephenson, John. "Multilevel generalised linear modelling and competing risks multistate survival analysis modelling of childhood caries." Thesis, Cardiff University, 2009. http://eprints.hud.ac.uk/7910/.

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There has been an ongoing debate regarding appropriate strategies for the management of carious primary teeth. Studies appear to provide evidence that both selective, symptom-based interventions and traditional restorative strategies are advantageous. However, the analysis and quantification of childhood caries may be affected by clustering of data, and the concurrent risk of exfoliation of primary teeth. Multilevel generalised linear models for the occurrence of primary caries were derived utilising data from a cohort study of 2,654 children aged 4-5 years at baseline undertaken 1999-2003. These models, which assumed underlying hierarchies with clustering at child, tooth and surface levels, identified higher rates of caries occurrence in primary molar teeth to be associated with boys, poor socio-economic background, lack of water fluoridation, 2nd mandibular molars and occlusal surfaces. Significant risk factors identified were carried forward for inclusion in parametric competing risks multivariate multilevel survival models, utilising cohort study data augmented with Dental Practice Board treatment data. Analysis of sound teeth and surfaces found the concurrent risk of exfoliation did not alter inferences of parameter significance, but restricted the extent of caries occurrence and reduced distinction in survival experience between different types of teeth and surfaces in children from different demographic backgrounds. Further competing risks survival models were derived to analyse the same teeth and surfaces in the untreated carious and filled states, to assess the effect of restorative treatment on subsequent exfoliation and extraction. Survival rates extrapolated to 14 years without further treatment for filled molar teeth were approximately double those of untreated teeth. Time of caries occurrence and treatment also affected survival, with later occurrence or treatment of caries associated with higher survival rates. However, early filling of carious teeth resulted in the greatest reductions in the expected time that decay is present in the mouth.
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Books on the topic "Generalized Linear Modelling"

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Fahrmeir, L. Multivariate statistical modelling based on generalized linear models. New York: Springer-Verlag, 1994.

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Fahrmeir, Ludwig, and Gerhard Tutz. Multivariate Statistical Modelling Based on Generalized Linear Models. New York, NY: Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4899-0010-4.

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Fahrmeir, Ludwig, and Gerhard Tutz. Multivariate Statistical Modelling Based on Generalized Linear Models. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3454-6.

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Stevan, Pilipović, and Scarpalézos D, eds. The linear theory of Colombeau generalized functions. Harlow: Longman, 1998.

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Adejumo, Adebowale Olusola. Modelling generalized linear (loglinear) models for raters agreement measure: With complete and missing values cases. New York: Peter Lang, 2006.

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(Editor), Brian Francis, Mick Green (Editor), and Clive Payne (Editor), eds. The GLIM System: Release 4 Manual (Generalized Linear Interactive Modelling). Oxford University Press, USA, 1993.

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(Assistant), W. Hennevogl, ed. Multivariate Statistical Modelling Based on Generalized Linear Models (Springer Series in Statistics). Springer, 2001.

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Nedeljkov, M., S. Pilipovic, and D. Scarpalezos. Linear Theory of Colombeau Generalized Functions (Research Notes in Mathematics Series). Chapman & Hall/CRC, 1998.

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Modelling Generalized Linear-loglinear Models for Raters Agreement Measure: With Complete And Missing Values Cases (Anwendungsorientierte Statistik). Peter Lang Publishing, 2005.

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Modelling Generalized Linear-loglinear Models for Raters Agreement Measure: With Complete And Missing Values Cases (Anwendungsorientierte Statistik, Bd. 9). Peter Lang Publishing, 2005.

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Book chapters on the topic "Generalized Linear Modelling"

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McCullagh, P., and J. A. Nelder. "Joint modelling of mean and dispersion." In Generalized Linear Models, 357–71. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4899-3242-6_10.

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Quicke, Donald, Buntika A. Butcher, and Rachel Kruft Welton. "More generalized linear modelling." In Practical R for biologists: an introduction, 171–86. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0171.

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Abstract This chapter employs generalized linear modelling using the function glm when we know that variances are not constant with one or more explanatory variables and/or we know that the errors cannot be normally distributed, for example, they may be binary data, or count data where negative values are impossible, or proportions which are constrained between 0 and 1. A glm seeks to determine how much of the variation in the response variable can be explained by each explanatory variable, and whether such relationships are statistically significant. The data for generalized linear models take the form of a continuous response variable and a combination of continuous and discrete explanatory variables.
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Quicke, Donald, Buntika A. Butcher, and Rachel Kruft Welton. "More generalized linear modelling." In Practical R for biologists: an introduction, 171–86. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0015.

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Abstract This chapter employs generalized linear modelling using the function glm when we know that variances are not constant with one or more explanatory variables and/or we know that the errors cannot be normally distributed, for example, they may be binary data, or count data where negative values are impossible, or proportions which are constrained between 0 and 1. A glm seeks to determine how much of the variation in the response variable can be explained by each explanatory variable, and whether such relationships are statistically significant. The data for generalized linear models take the form of a continuous response variable and a combination of continuous and discrete explanatory variables.
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Longford, N. T. "Statistical Modelling of Data from Hierarchical Structures Using Variance Component Analysis." In Generalized Linear Models, 112–19. New York, NY: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4615-7070-7_12.

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Verbeek, Albert. "The compactification of generalized linear models." In Statistical Modelling, 314–27. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3680-1_36.

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Wixley, R. A. J. "Uses of Power Transformation in Generalized Linear Modeling." In Statistical Modelling, 328–35. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3680-1_37.

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Wortha, H. P. "MIVA: An Alternative Method to Generalized Linear Models." In Statistical Modelling, 336–43. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3680-1_38.

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Cole, Michael J., and John W. McDonald. "Bootstrap Goodness-of-Link Testing in Generalized Linear Models." In Statistical Modelling, 84–94. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3680-1_10.

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Carroll, Raymond J., Xihong Lin, and Naisyin Wang. "Generalized Linear Mixed Measurement Error Models." In Modelling Longitudinal and Spatially Correlated Data, 321–30. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-0699-6_28.

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Eilers, Paul H. C., and Brian D. Marx. "Generalized Linear Models with P-splines." In Advances in GLIM and Statistical Modelling, 72–77. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-2952-0_12.

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Conference papers on the topic "Generalized Linear Modelling"

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"Statistical downscaling of extreme rainfall from CMIP5 in the Onkaparinga catchment using a generalized linear model." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.l5.rashid.

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de Faverges, M. M., G. Russolillo, C. Picouleau, B. Merabet, and B. Houzel. "Modelling passenger train arrival delays with Generalized Linear Models and its perspective for scheduling at main stations." In 8th International Conference on Railway Engineering (ICRE 2018). Institution of Engineering and Technology, 2018. http://dx.doi.org/10.1049/cp.2018.0049.

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Landmann, Tobias, Olena Dubovyk, Gohar Ghazaryan, Jackson Kimani, and Elfatih Abdel-Rahman. "Wide-area mapping of invasive species propagation and containment zones in somaliland using phenometric trends and generalized linear modelling." In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2017. http://dx.doi.org/10.1109/igarss.2017.8127149.

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Rahimi, H. N., M. H. Korayem, and A. Nikoobin. "Optimal Motion Planning of Manipulators With Elastic Links and Joints in Generalized Point-to-Point Task." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87759.

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Finding optimal trajectory is critical in several applications for robots from payload transport between two given states in a prescribed time such that a cost functional is minimized. This paper is concerned with the path planning of flexible robotic arms in point-to-point motion, based on indirect solution of optimal control problem. Dynamic modelling technique based on the combined Euler–Lagrange formulation and assumed modes method is applied, then by implementing the Pontryagin’s minimum principle; necessary conditions for optimality are derived. Nonlinear states and control constraints are treated without any simplifications or transforming them into sequences of systems with linear equations. By these means, the modelling of the complete optimal control problem and the accompanying boundary value problem is automated to a great extent. Finally, the performance of method is illustrated through the computer simulations.
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Combes, J. F., J. P. Chabard, and B. Metivet. "3D Flow Analysis in a Linear Cascade Using a Navier-Stokes Finite Element Code." In ASME 1990 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1990. http://dx.doi.org/10.1115/90-gt-302.

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In order to solve industrial flow problems in complex geometries, a finite element code, N3S, has been developped at Electricité de France. For an incompressible unsteady flow, the Reynolds-averaged Navier-Stokes equations, with a k-ε turbulence modelling, are split into a set of equations for transport, for diffusion and a Generalized Stokes Problem. In this paper, we briefly describe the algorithms chosen to solve each step, the k-ε treatment and the boundary conditions (wall functions). We present also the results of a flow calculation in a linear cascade at normal and high incidence and compare them with the measurements of Yamamoto (ASME papers 86-GT-185 and 88-GT-110). The main flow features and the secondary flows (i.e., the passage and the horseshoe vortex) are qualitatively well predicted by the code but some discrepancies exist in the prediction of the losses.
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Krodkiewski, Janusz M., and Gregory J. Davies. "Modelling a New Three-Pad Active Bearing." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-54322.

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This paper describes investigations into a new type of active bearing to be implemented in the field of rotating machinery. Active bearings are based on the concept that journal oil flow can be modified during operation by active devices. Here, the concepts of the flexible pads and the oil-filled chambers that control their deflection are used. Three active pads are positioned around the journal with three oil-filled chambers positioned behind them. One of them, the load-bearing pad located at the bottom of the bearing, acts as a passive device and is equipped with a very thin film chamber, which acts as a source of damping. Such a damper was found in previous work to be effective in dissipating energy. Here, in a departure from previous work, two additional small pads with deep oil-filled chambers have been added in order to allow control theory to be implemented. They are located in the upper part of the active bearing. A non-linear system model is developed for the rotor-bearing system that includes the described active bearing. The flow inside the upper chambers that control motion of the active pads was neglected due to their large volume. It results in a uniform pressure distribution along the upper pads. The pressure distribution within the damper oil film (inside the lower chamber) and the journal oil film was modeled with the aid of the Reynolds equation. They were solved by means of the finite difference method and Gauss-Seidel technique. The same mesh used for solution of the Reynolds equation was used for the division of the flexible pads into the finite elements. The same approach was adopted for the modelling of the dynamic properties of the rotor. The mass and stiffness matrices for the pads and rotor were condensed down to 12 master generalized coordinates using Guyan condensation. The obtained system of matrix equations was converted to a system of first order equations and solved via the Runge-Kutta method. Some results of the numerical testing of the mathematical model developed are provided.
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"Generalised linear model and analysis of cereal plant biomass." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.b1.cespedes.

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Combourieu, Adrien, Maxime Philippe, François Rongère, and Aurélien Babarit. "InWave: A New Flexible Design Tool Dedicated to Wave Energy Converters." In ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/omae2014-24564.

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This article presents the novel methodology used in the software InWave to address the problem of wave energy converters (WEC) modelling. The originality compared to other recently developed tools lies in a fast semi-recursive multibody dynamic solver which integrates a flexible hydrodynamic solver. The multibody solver works in time domain and is fully nonlinear. It solves the dynamic of systems formed of a fixed or free base articulated with any number of bodies that can be floating or not, with branchy structure ([1]). The integrated hydrodynamic solver is a linear potential flow solver based on boundary elements method. It uses the generalized degrees of freedom approach ([11]). Combined with a relative coordinate parameterization, it allows for a minimization of the number of hydrodynamic boundary value problems that have to be solved, thus allowing a reduction of computational time both for BEM computations and time domain simulations. Time domain reconstruction is performed to link hydrodynamic loads with the multibody dynamic solver. Interaction between bodies through radiation is thus taken into account. InWave is a complete WEC modelling tool including incident wave generation, multibody dynamic solver, hydrodynamic solver, power take-off and mooring models, post-processing and visualization. A successful comparison with the linear potential flow solver Aquaplus ([5]) on a basic cylinder test case is carried out. Finally, a complex test case on a Langlee-like device is presented, comparing InWave results with those from the NumWec project ([2]). A good agreement between both models is found, which increases the confidence in InWave algorithms and implementation.
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Habchi, W., D. Eyheramendy, S. Bair, P. Vergne, and G. Morales-Espejel. "A Finite Element Approach of the Fully Coupled Elastohydrodynamic Problem." In ASME/STLE 2007 International Joint Tribology Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/ijtc2007-44200.

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Up to now, most of the numerical works dealing with the modelling of the isothermal elastohydrodynamic problem were based on a weak coupling resolution of the Reynolds and elasticity equations (semi-system approach). The latter were solved separately using a Finite Difference discretization. Very few authors attempted to solve the problem in a fully coupled way, thus solving both equations simultaneously (full-system approach). These attempts suffered from a major drawback which is the almost full Jacobian matrix of the non-linear system of equations. This work presents a new approach for solving the fully coupled isothermal elastohydrodynamic problem using a Finite Element discretization of the corresponding equations. The complexity is the same as for classical algorithms, but with an improved convergence rate, a reduced size of the problem and a regular sparse Jacobian matrix. This method is applied to the case of a Generalized Newtonian lubricant using a powerful shear-thinning model. The results are compared with experimental data.
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Kidikian, John, and Marcelo Reggio. "Off-Design Prediction of Transonic Axial Compressors: Part 2 — Generalized Mean-Line Loss Modelling Methodology." In ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/gt2018-75125.

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In Part 1, of this two-part paper, an off-design mean-line code and a generalized methodology to obtain “tuning” factors were presented. It was shown that the modified factors were capable of predicting the off-design performance of four well documented NASA transonic axial compressors. In this paper, Part 2, a generalized methodology to create correlations for the rotor and stator total pressure losses, deviation angles, and blade row inlet and exit blockage factors is presented. The generalized mean-line loss modelling methodology will allow the compressor designer to decommission the use of the performance map scaling techniques. In its place, the generalized predictive methodology will accurately estimate the off-design performance of transonic axial compressors and can be used to fill the gaps of missing data.
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