Results 21 to 30 of about 141,753 (193)
Boosting insights in insurance tariff plans with tree-based machine learning methods [PDF]
, 2020 Pricing actuaries typically operate within the framework of generalized linear models (GLMs). With the upswing of data analytics, our study puts focus on machine learning methods to develop full tariff plans built from both the frequency and severity of ...
Antonio, Katrien +3 more
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ESTIMASI CADANGAN KLAIM MENGGUNAKAN GENERALIZED LINEAR MODEL (GLM) DAN COPULA
Jurnal Gaussian, 2020 In the articles of this will be discussed regarding the estimated reserves of the claim using the Generalized Linear Model (GLM) and Copula. Copula is a pair function distribution marginal becomes a function of distribution of multivariate. The use of copula regression in this article is to produce estimated reserves of claims. Generalized Linear Model
Yuciana Wilandari +2 more
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Journal of Water and Soil Science, 2023 Introducing reliable regional models to predict the maximum discharge of floods using characteristics of sub-basins has special importance in terms of flood management and designing hydraulic structures in basins that have no hydrometric station. The present study has tried to provide appropriate regional flood models using generalized linear models ...
P. Mohit-Isfahanii, V. Chitsaz
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Wiggles and Curves: The Analysis of Ordinal Patterns
Problemy Zarządzania, 2016 Almost all social science data are analysed with variants of the General Linear Model (GLM): regression analyses, analyses of variance, factor analyses, path analyses and the like.
Warren Thorngate, Chunyun Ma
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A Note on Heteroskedasticity Issues [PDF]
, 1992 The purpose of this paper is to clarify certain issues related to the incidence of heteroskadisticity in the General Linear Model (GLM); to provide simpler and more accessible proofs for a number of propositions, and to allow the results to stand under ...
Dhrymes, Phoebus J.
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The Detection of Metabolite-Mediated Gene Module Co-Expression Using Multivariate Linear Models. [PDF]
PLoS ONE, 2016 Investigating whether metabolites regulate the co-expression of a predefined gene module is one of the relevant questions posed in the integrative analysis of metabolomic and transcriptomic data.
Trishanta Padayachee +5 more
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Improving the analysis of near-infrared spectroscopy data with multivariate classification of hemodynamic patterns: a theoretical formulation and validation [PDF]
, 2018 Objective. The statistical analysis of functional near infrared spectroscopy (fNIRS) data based on the general linear model (GLM) is often made difficult by serial correlations, high inter-subject variability of the hemodynamic response, and the presence
Barbour, Randall L. +4 more
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Task failure prediction for wafer-handling robotic arms by using various machine learning algorithms
Measurement + Control, 2021 Industries are increasingly adopting automatic and intelligent manufacturing in production lines, such as those of semiconductor wafers, optoelectronic devices, and light-emitting diodes.
Ping Wun Huang, Kuan-Jung Chung
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Independent component analysis of interictal fMRI in focal epilepsy: comparison with general linear model-based EEG-correlated fMRI [PDF]
, 2007 The general linear model (GLM) has been used to analyze simultaneous EEG–fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG.
Carmichael, D.W. +7 more
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International Journal of Biomedical Imaging, 2009 As a consequence of misspecification of the hemodynamic response and noise variance models, tests on general linear model coefficients are not valid. Robust estimation of the variance of the general linear model (GLM) coefficients in fMRI time series is ...
Lourens Waldorp
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