Results 231 to 240 of about 58,672 (256)

Comparison of linear predictors obtained by data transformation, generalized linear models (GLM) and response modeling methodology (RMM)

Quality and Reliability Engineering International, 2007
AbstractThe data‐transformation approach and generalized linear modeling both require specification of a transformation prior to deriving the linear predictor (LP). By contrast, response modeling methodology (RMM) requires no such specifications. Furthermore, RMM effectively decouples modeling of the LP from modeling its relationship to the response ...
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Generalized linear model multivariate poisson with artificial marginal (GLM-MPAM): Application of vehicle insurance

AIP Conference Proceedings, 2019
At vehicle insurance companies, the determination of the appropriate pure premium will make the business run well. In this study, we were modeling claims frequency data by considering the characteristics of policyholder such as policyholder’s age, marital status, sex, car engine capacity, and age.
null Jamilatuzzahro, Rezzy Eko Caraka, Dedi Aprinaldy, Asma Mahadi   +3 more
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Statistical Downscaling of Precipitation in the Upper Nile: Use of Generalized Linear Models (GLMs) for the Kyoga Basin

2014
General circulation model (GCM) climate projections cannot be relied on to provide information at scales finer than the GCM model-grid resolutions; hence, fine-scale information can be achieved by the use of high spatial resolution in dynamical models or empirical statistical downscaling.
Kigobe, M., Wheater, H., McIntyre, N.
openaire   +2 more sources

Statistical analysis of stability data by means of general linear models (GLM)

Drug Development and Industrial Pharmacy, 1991
AbstractApplication of a General Linear Model (GLM, “Analysis of Covariance”) to the statistical interpretation of stability data combines the methods of regression and analysis of variance in one common model. Expanding the well accepted method of linear regression upon time, the GLM model permits one to include supportive factors which may be either ...
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Application of the General Linear Model (GLM) and Operations Research (OR) Models to the Optimization of Field Exploration and Development Planning

1987
It is well recognized that there are important relationships between quantitative or quantified geo-variates and the geological, geophysical and geochemical environment of mineral deposits, some of which are diagnostic of the occurrence of ore. However, since there is still much uncertainty as to the precise nature of these relationships, we are ...
T. K. Wignall, J. De Geoffroy
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Application of General Linear Modeling (GLM) to analysis of indentation in compact bone

2012
The indentation process is useful in determining the behavior of a material under the action of a point or line load. The main geometric features of a wedge shaped indenter are the wedge angle and the radius on the wedge apex. General Linear Modeling is a statistical linear regression model which may be stated as: Y= β0+β1Xi1+β2X i2+β3Xi3+β4X i1Xi2 ...
Reilly, Ger, Taylor, David
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PREMIUM PRICING AND RISK ASSESSMENT FOR CLAIM AMOUNTS BASED ON GENERALIZED LINEAR MODELS (GLM)

2013
ActuarialScience is described as a mechanism that decreases the negative financialeffects of random events which becomes obstacles to actualize reasonableexpectations. It is important subject to make a fair share for the same amountof money which is paid by the people who has the same risk.
Sarul, Latife Sinem, Balaban, Mehmet Erdal   +1 more
openaire   +1 more source

Evaluating the Performance of the Generalized Linear Model (glm) R Package Using Single-Cell RNA-Sequencing Data

Applied Sciences (Switzerland), 2023
Omar Alaqeeli
exaly  

An explicit split point procedure in model-based trees allowing for a quick fitting of GLM trees and GLM forests

Statistics and Computing, 2021
Christophe Dutang, Quentin Guibert
exaly  

Linear Models, Generalized Linear Models (GLMs), and Random Effects Models

2016
Marc Kéry, J. Andrew Royle
openaire   +1 more source