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generalized linear model (GLM)

EXTRACTION OF RETINAL BLOOD VESSEL BY COMBINING GABOR FILTER AND GENERALIZED LINEAR MODEL

EXTRACTION OF RETINAL BLOOD VESSEL BY COMBINING GABOR FILTER AND GENERALIZED LINEAR MODEL

... and Generalized Linear Model (GLM) for extraction of blood vessels of retina, with this use clarity in extraction can be ...and generalized linear model from retinal ...

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A generalized linear model with smoothing effects for claims reserving

A generalized linear model with smoothing effects for claims reserving

... popular Generalized Linear Model (GLM) introduced in a claims reserving context by Renshaw & Verrall ...This model enables us to smooth origin, development and calendar year parameters in ...

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A Signal-to-Noise Ratio Estimator for Generalized Linear Model Systems

A Signal-to-Noise Ratio Estimator for Generalized Linear Model Systems

... for generalized linear model systems We extend the SNR definitions presented in the previous sections to Generalized Linear Model (GLM) ...any model in the exponential ...

7

Measurement errors in generalized linear model explanatory variables

Measurement errors in generalized linear model explanatory variables

... Under the assumption that response and explanatory variables follow a generalized linear model, estimating equations are derived for the case in which the explanatory variables are measu[r] ...

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Application of Generalized Linear Model to the Minimization of Defectives in Sewing Process of Apparel Industry

Application of Generalized Linear Model to the Minimization of Defectives in Sewing Process of Apparel Industry

... the Generalized Linear Model was used by considering the gamma ...full model was fitted for each defect ...for generalized linear models can be characterized by the deviance ...

6

Nested Generalized Linear Model with Ordinal  Response for Correlated Data

Nested Generalized Linear Model with Ordinal Response for Correlated Data

... assumed model for the variances and within-subject associations; unless they have been correctly modeled, our model for the covariance matrix may not be ...build generalized linear ...

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The Equivalence of the Maximum Likelihood and a Modified Least Squares for a Case of Generalized Linear Model

The Equivalence of the Maximum Likelihood and a Modified Least Squares for a Case of Generalized Linear Model

... the generalized linear models (GLM), Mc Cullagh and Nelder1989, and on the estimate of quasi- likelihood (QL) developed by Wedderburn 1974, was a great alternative and which leads thereafter to the ...

5

Vol 6, No 8 (2015)

Vol 6, No 8 (2015)

... to model the actual data rather than data that are transformed (fitted) to meet ...Regression Model (LRM) which is a type of the Generalized Linear Model (GLM) is appropriate in this ...

6

Plotting partial correlation and regression in ecological studies

Plotting partial correlation and regression in ecological studies

... General linear model (GLM) and the Generalized linear model (GLZ) are widely used in ...simple linear regression can be easily extended to these multivariate techniques in plots ...

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Detecting Diabetes Mellitus using Machine Learning Ensemble

Detecting Diabetes Mellitus using Machine Learning Ensemble

... not: Linear Discriminant Analysis, Support Vector Machine and Naïve ...and Generalized Linear model, then a stacking ensemble is built aiming at achieving a better accuracy and f-measure by ...

8

Brood sex ratio in the Yellow-bellied Prinia (Prinia flaviventris)

Brood sex ratio in the Yellow-bellied Prinia (Prinia flaviventris)

... A generalized linear model with binomial error structure and a general linear mixed model (when the response has a normal distribution) were used to analyze the effects of different ...

7

Comparison of HDNN with other Machine Learning Models in Stock Market Prediction

Comparison of HDNN with other Machine Learning Models in Stock Market Prediction

... learning model has been developed in this research which is the combination of a deep neural network and the fuzzy inference ...This model is termed in this paper as Hybrid Deep Neural Network ...this ...

9

Generalized Linear Models in Vehicle Insurance

Generalized Linear Models in Vehicle Insurance

... best model for an estimation of insurance ...a generalized linear model (GLM) is ...the model for the best estimate of annual claim frequency is ...

6

The influence of cold weather on the usage of emergency link calls: a case study in Hong Kong

The influence of cold weather on the usage of emergency link calls: a case study in Hong Kong

... Poisson generalized linear model (GLM) with polynomial effect functions of relevant ...Poisson generalized linear autoregressive moving average (GLARMA) model is refitted to the ...

9

A Simple Mechanism for Beyond-Pairwise Correlations in Integrate-and-Fire Neurons

A Simple Mechanism for Beyond-Pairwise Correlations in Integrate-and-Fire Neurons

... (DG) model of [1, 14]. The success of the DG model in capturing EIF population statistics is significant for two ...abstracted model has been able to capture the population output recorded from ...

13

Binarsity: a penalization for one-hot encoded features in linear supervised learning

Binarsity: a penalization for one-hot encoded features in linear supervised learning

... of linear supervised ...extra linear constraint, on the weights of a generalized linear model trained on a binarization of the raw continuous features, leading to a procedure that ...

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Designs for generalized linear models with several variables and model uncertainty

Designs for generalized linear models with several variables and model uncertainty

... Sections 3 and 5, where it is shown that the methods in this paper have advantages over the use of standard factorial designs. A further example from our own consulting is an investigation by a food manufacturing ...

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An Application of Bootstrapping in Logistic Regression Model

An Application of Bootstrapping in Logistic Regression Model

... regression model and estimate the probability of infection as function of age using a Generalized Linear Model for binary data, construct 95% confidence intervals for the unknown parameters of ...

9

Using generalized linear models to model compositional response data

Using generalized linear models to model compositional response data

... to model longitudinal data, where the working cor- relation structure is used to cater for the correlation which arises between the responses that are achieved over ...a generalized linear ...

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Thirteenth Industrial Mathematical and Statistical Modeling Workshop for graduate students

Thirteenth Industrial Mathematical and Statistical Modeling Workshop for graduate students

... mouse model study of the relationship of dose levels to papilloma formation caused by 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD), a ubiquitous environmental ...

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