Bayesian binary regression with exponential power link

2014 ◽  
Vol 71 ◽  
pp. 464-476 ◽  
Author(s):  
L. Naranjo ◽  
J. Martín ◽  
C.J. Pérez
Keyword(s):  
Binary Regression ◽  
Exponential Power

scholarly journals Polyconvex hyperelastic modeling of rubberlike materials

2021 ◽  
Vol 43 (7) ◽  
Author(s):  
Cyprian Suchocki ◽  
Stanisław Jemioło
Keyword(s):  
Experimental Data ◽  
Power Law ◽  
Curve Fitting ◽  
Constitutive Relations ◽  
Data Sets ◽  
Power Law Model ◽  
Stored Energy ◽  
Data Approximation ◽  
Exponential Power ◽  
Hyperelastic Models

AbstractIn this work a number of selected, isotropic, invariant-based hyperelastic models are analyzed. The considered constitutive relations of hyperelasticity include the model by Gent (G) and its extension, the so-called generalized Gent model (GG), the exponential-power law model (Exp-PL) and the power law model (PL). The material parameters of the models under study have been identified for eight different experimental data sets. As it has been demonstrated, the much celebrated Gent’s model does not always allow to obtain an acceptable quality of the experimental data approximation. Furthermore, it is observed that the best curve fitting quality is usually achieved when the experimentally derived conditions that were proposed by Rivlin and Saunders are fulfilled. However, it is shown that the conditions by Rivlin and Saunders are in a contradiction with the mathematical requirements of stored energy polyconvexity. A polyconvex stored energy function is assumed in order to ensure the existence of solutions to a properly defined boundary value problem and to avoid non-physical material response. It is found that in the case of the analyzed hyperelastic models the application of polyconvexity conditions leads to only a slight decrease in the curve fitting quality. When the energy polyconvexity is assumed, the best experimental data approximation is usually obtained for the PL model. Among the non-polyconvex hyperelastic models, the best curve fitting results are most frequently achieved for the GG model. However, it is shown that both the G and the GG models are problematic due to the presence of the locking effect.

Bayesian outlier analysis in binary regression

2010 ◽  
Vol 37 (8) ◽  
pp. 1355-1368 ◽  
Author(s):  
Aparecida D.P. Souza ◽  
Helio S. Migon
Keyword(s):  
Outlier Analysis ◽  
Binary Regression

Design effects for binary regression models fitted to dependent data

1993 ◽  
Vol 12 (13) ◽  
pp. 1259-1268 ◽  
Author(s):  
John M. Neuhaus ◽  
Mark R. Segal
Keyword(s):  
Regression Models ◽  
Dependent Data ◽  
Binary Regression ◽  
Design Effects

Determination of Spread Activation Energy and Assessment of Wetting Behavior of Solders on Metallic Substrates

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
K. N. Prabhu ◽  
G. Kumar
Keyword(s):  
Surface Roughness ◽  
Operating Temperature ◽  
Substrate Surface ◽  
Substrate Material ◽  
Metallic Substrates ◽  
Wetting Behavior ◽  
Substrate Surface Roughness ◽  
Exponential Power ◽  
Kinetics Of

The effects of substrate material, substrate surface roughness, and operating temperature on the wetting behavior of Sn–37Pb, Sn–3.5Ag, and Sn–9Zn eutectic solders on metallic substrates were investigated. Solder spreading kinetics was successfully represented by the exponential power law (EPL): ϕ=exp(−Kτn). The EPL parameter K has the significance of accelerating the kinetics of relaxation while the parameter n represents the resistance to spreading process (spread resistance parameter). EPL parameters exhibited a decreasing trend with an increase in surface roughness. Estimated activation energies for solder spreading were found to be in between those reported for inert and highly reactive spreading systems.

scholarly journals Application of Binary Regression Analysis in the Prescription Pattern of Antidepressants

2013 ◽  
Vol 1 (1) ◽  
pp. 19
Author(s):  
Indrajit Banerjee ◽  
Indranil Banerjee ◽  
Bedanta Roy ◽  
Brijesh Sathian
Keyword(s):  
Regression Analysis ◽  
Binary Regression ◽  
Prescription Pattern ◽  
Binary Regression Analysis

scholarly journals KONDISI LINGKUNGAN, PERILAKU HIDUP SEHAT, DAN STATUS KESEHATAN BALITA DI INDONESIA

Populasi ◽  
2016 ◽  
Vol 22 (1) ◽  
pp. 76-86
Author(s):  
Sumini Sumini ◽  
Jevri Ardiansyah
Keyword(s):  
Data Analysis ◽  
Health Status ◽  
Health Survey ◽  
Good Condition ◽  
Secondary Data ◽  
Demographic And Health Survey ◽  
Questionnaire Data ◽  
Binary Regression ◽  
Healthy Life ◽  
House Condition

This research aims to study the enviromental condition, healthy life behaviour of mothers and health status of children in Indonesia. This research uses secondary data analysis from Indonesia Demographic and Health Survey 2007. Three main indicators in here are the house condition which sourced from household quesionnaire, healthy life behaviour of mothers and health status of children which sourced from ever married women’s questionnaire. Data was processes and analyzed with desriptive statistic, inference and binary regression. One of the result is that some houses were in good condition although some still did not have latrine facility. Mothers also had performed a healthy life behaviour, such as washing hands before preparing food and did not smoke.Tujuan penelitian ini adalah mengkaji kondisi lingkungan tempat tinggal, perilaku hidup sehat ibu, dan status kesehatan balita di Indonesia. Penelitian ini menggunakan analisis data sekunder dari Survei Demografi dan Kesehatan Indonesia 2007. Tiga indikator utama yang digunakan adalah kondisi tempat tinggal yang diambil dari daftar pertanyaan rumah tangga, perilaku hidup sehat ibu dan status kesehatan balita yang diambil dari daftar pertanyaan perempuan pernah kawin. Data diolah dan dianalisis dengan statistik deskriptif, inferensi, dan regresi binari. Salah satu hasil penelitian ini adalah kondisi tempat tinggal cukup baik walaupun ada yang belum memiliki jamban. Ibu pun terbiasa berperilaku sehat, seperti terbiasa mencuci tangan sebelum mengelola makanan dan tidak merokok.

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