Testing for Genuine Multimodality in Finite Mixture Models: Application to Linear Regression Models

2007 ◽  
pp. 209-216 ◽  
Author(s):  
Bettina Grün ◽  
Friedrich Leisch
Keyword(s):  
Linear Regression ◽  
Mixture Models ◽  
Regression Models ◽  
Finite Mixture Models ◽  
Finite Mixture ◽  
Linear Regression Models

scholarly journals The use of finite mixture models to examine the serum 25(OH)D levels among Saudis

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260748
Author(s):  
Ibrahim Al-Sumaih ◽  
Michael Donnelly ◽  
Ciaran O’Neill
Keyword(s):  
Linear Regression ◽  
Mixture Models ◽  
Finite Mixture Models ◽  
Unobserved Heterogeneity ◽  
Finite Mixture ◽  
Latent Classes ◽  
Class Iii ◽  
Interview Survey ◽  
The Relationship

Background Recorded serum 25(OH)D in survey data varies with observed and unobserved respondent characteristics. The aim of this study was to expose latent population sub-groups and examine variation across groups regarding relationships between serum 25(OH)D and observable characteristics. Methods This study explored the role of unobserved heterogeneity on associations between surveyed 25(OH)D and various factors using a sample (n = 2,641) extracted from the Saudi Health Interview Survey (2013). Linear regression and finite mixture models (FMM) were estimated and compared. The number of latent classes in the FMM was chosen based on BIC score. Result Three latent classes were identified. Class I (39.82%), class II (41.03%), and class III (19.15%) with mean 25(OH)D levels of 22.79, 34.88, and 57.45 ng/ml respectively. Distinct patterns of associations with nutrition, behaviour and socio-demographic variables were recorded across classes that were not revealed in pooled linear regression. Conclusion FMM has the potential to provide additional insights on the relationship between 25(OH)D levels and observable characteristics. It should be more widely considered as a method of investigation in this area.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Linear Regression Models for Interval-Valued Data using Log-transformation

2020 ◽  
Author(s):  
Nykolas Mayko Maia Barbosa ◽  
João Paulo Pordeus Gomes ◽  
César Lincoln Cavalcante Mattos ◽  
Diêgo Farias Oliveira
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Log Transformation ◽  
Interval Valued

THE PREDICTIVE CONTENT OF DISAGGREGATED NORMAL INCOME: An Empirical Study in the JSX

2003 ◽  
Vol 5 (3) ◽  
pp. 363 ◽  
Author(s):  
Slamet Sugiri
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Stock Exchange ◽  
Manufacturing Firms ◽  
Single Step ◽  
Model Parameters ◽  
Linear Regression Models ◽  
Operating Income ◽  
Predictive Content ◽  
Multiple Step

The main objective of this study is to examine a hypothesis that the predictive content of normal income disaggregated into operating income and nonoperating income outperforms that of aggregated normal income in predicting future cash flow. To test the hypothesis, linear regression models are developed. The model parameters are estimated based on fifty-five manufacturing firms listed in the Jakarta Stock Exchange (JSX) up to the end of 1997.This study finds that empirical evidence supports the hypothesis. This evidence supports arguments that, in reporting income from continuing operations, multiple-step approach is preferred to single-step one.

scholarly journals A Finite Mixture Modelling Perspective for Combining Experts’ Opinions with an Application to Quantile-Based Risk Measures

Risks ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 115
Author(s):  
Despoina Makariou ◽  
Pauline Barrieu ◽  
George Tzougas
Keyword(s):  
Decision Making ◽  
Mixture Models ◽  
Finite Mixture Models ◽  
Risk Measures ◽  
Finite Mixture ◽  
Parametric Family ◽  
Collective Decision Making ◽  
Multiple Sources ◽  
Mixture Modelling ◽  
Expert Opinions

The key purpose of this paper is to present an alternative viewpoint for combining expert opinions based on finite mixture models. Moreover, we consider that the components of the mixture are not necessarily assumed to be from the same parametric family. This approach can enable the agent to make informed decisions about the uncertain quantity of interest in a flexible manner that accounts for multiple sources of heterogeneity involved in the opinions expressed by the experts in terms of the parametric family, the parameters of each component density, and also the mixing weights. Finally, the proposed models are employed for numerically computing quantile-based risk measures in a collective decision-making context.

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