Limitations and performance of three approaches to Bayesian inference for Gaussian copula regression models of discrete data

2021 ◽  
Author(s):  
L. L. Henn
Keyword(s):  
Bayesian Inference ◽  
Regression Models ◽  
Discrete Data ◽  
Gaussian Copula ◽  
And Performance

scholarly journals Revisiting Gaussian copulas to handle endogenous regressors

2021 ◽  
Author(s):  
Jan-Michael Becker ◽  
Dorian Proksch ◽  
Christian M. Ringle
Keyword(s):  
Regression Models ◽  
Statistical Power ◽  
Multilevel Models ◽  
Gaussian Copula ◽  
Simulation Studies ◽  
Validity Of Results ◽  
Endogenous Regressors ◽  
Copula Approach ◽  
Original Presentation ◽  
And Performance

AbstractMarketing researchers are increasingly taking advantage of the instrumental variable (IV)-free Gaussian copula approach. They use this method to identify and correct endogeneity when estimating regression models with non-experimental data. The Gaussian copula approach’s original presentation and performance demonstration via a series of simulation studies focused primarily on regression models without intercept. However, marketing and other disciplines’ researchers mainly use regression models with intercept. This research expands our knowledge of the Gaussian copula approach to regression models with intercept and to multilevel models. The results of our simulation studies reveal a fundamental bias and concerns about statistical power at smaller sample sizes and when the approach’s primary assumptions are not fully met. This key finding opposes the method’s potential advantages and raises concerns about its appropriate use in prior studies. As a remedy, we derive boundary conditions and guidelines that contribute to the Gaussian copula approach’s proper use. Thereby, this research contributes to ensuring the validity of results and conclusions of empirical research applying the Gaussian copula approach.

Efficient Bayesian inference for Gaussian copula regression models

Biometrika ◽  
2006 ◽  
Vol 93 (3) ◽  
pp. 537-554 ◽  
Author(s):  
Michael Pitt ◽  
David Chan ◽  
Robert Kohn
Keyword(s):  
Bayesian Inference ◽  
Regression Models ◽  
Gaussian Copula

scholarly journals Bayesian inference of genetic parameters for reproductive and performance traits in White Leghorn hens

2018 ◽  
Vol 63 (No. 6) ◽  
pp. 230-236 ◽  
Author(s):  
J.O. Rosa ◽  
G.C. Venturini ◽  
T.C.S. Chud ◽  
B.C. Pires ◽  
M.E. Buzanskas ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Fixed Effects ◽  
Egg Production ◽  
Genetic Parameters ◽  
Laying Hens ◽  
Reproductive Traits ◽  
A Posteriori ◽  
White Leghorn ◽  
Performance Traits ◽  
And Performance

This study estimated the genetic parameters for reproductive and performance traits and determined which ones can be used as selection criteria for egg production in laying hens using the Bayesian inference. The data of 1894 animals from three generations of White Leghorn laying hens were analyzed for fertility (FERT), hatchability (HATC), and birth rate measurements at 60 weeks of age (BIRTH), body weight at 16 and 60 weeks of age (BW16 and BW60), age at sexual maturity (ASM), egg height/width ratio, weight, and density at 28, 36, and 40 weeks of age (RHW28, RHW36, RHW40, WEGG28, WEGG36, WEGG40, DENS28, DENS36, and DENS40, respectively) traits. The genetic parameters were estimated by the Bayesian inference method of multi-trait animal model. The model included the additive and residual genetic random effects and the fixed effects of generation. The a posteriori mean distributions of the heritability estimates for reproductive traits ranged from 0.14 ± 0.003 (HATC) to 0.22 ± 0.005 (FERT) and performance from 0.07 ± 0.001 (RHW28) to 0.42 ± 0.001 (WEGG40). The a posteriori mean distributions of the genetic correlation between reproductive traits ranged from 0.18 ± 0.026 (FERT and HACT) to 0.79 ± 0.007 (FERT and BIRTH) and those related to performance ranged from –0.49 ± 0.001 (WEGG36 and DENS36) to 0.75 ± 0.003 (DENS28 and DENS36). Reproductive and performance traits showed enough additive genetic variability to respond to selection, except for RHW28. This trait alone would have little impact on the genetic gain because environmental factors would have a higher impact compared to those from the additive genetic factors. Based on the results of this study, the selection applied on the BIRTH trait can be indicated to improve FERT and HATC of eggs. Furthermore, the use of the WEGG40 could improve egg quality in this population.

Semiparametric Bayesian inference for regression models

1999 ◽  
Vol 27 (4) ◽  
pp. 719-734 ◽  
Author(s):  
Yodit Seifu ◽  
Thomas A. Severini ◽  
Martin A. Tanner
Keyword(s):  
Bayesian Inference ◽  
Regression Models ◽  
Semiparametric Bayesian Inference

scholarly journals Corporate governance and firm performance: Evidence from an emerging market

2019 ◽  
Vol 9 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Ahmed S. Alanazi
Keyword(s):  
Corporate Governance ◽  
Firm Performance ◽  
Emerging Markets ◽  
Regression Models ◽  
Emerging Market ◽  
Operating Performance ◽  
Listed Firms ◽  
Developed Markets ◽  
Two Samples ◽  
And Performance

The paper investigates the link between corporate governance scores and firm performance among the largest 90 listed companies on the Saudi Stock market. The sample of 90 listed firms is split into two samples: firms with high governance scores and firms with low governance scores. The research compares and contrasts the operating performance of the two samples. In addition, regression models are used to test the link between governance scores and performance. No link between the companies’ corporate governance scores and operating performance is found. It is difficult to capture all elements of the complex corporate governance topic in corporate governance scores. It seems that corporate governance in emerging markets lags far behind that of developed markets. This is the first paper to examine the link between corporate governance scores and operating performance in the Saudi market, a new emerging market that has not been examined. The paper adds to the debate in the literature whether there is a link between corporate governance scores and performance. The evidence in the literature is inconclusive.

scholarly journals PENGARUH KODE ETIK APIP TERHADAP KINERJA AUDITOR PEMERINTAH PADA INSPEKTORAT PROVINSI MALUKU UTARA

2017 ◽  
Vol 12 (2) ◽  
Author(s):  
Engelita O. Kneefel ◽  
Jullie J. Sondakh ◽  
Lidia Mawikere
Keyword(s):  
Regression Models ◽  
Quantitative Method ◽  
Primary Data ◽  
Government Performance ◽  
Ethical Codes ◽  
Multiple Regression Models ◽  
Research Population ◽  
Independent Variable ◽  
The Government ◽  
And Performance

This research aims to and analyze the effect of APIP Ethical Codes (Integrity, Objectivity, Privacy, and Capability) through the performance of auditor in Maluku Utara Provincial Inspectorate which used quantitative method, with the multiple regression models. The research population is 44 Auditors and sampel is 44 Auditors. Primary data obtained by quistionaire distribution throughout 44 respondents which all fullfiled and operable. Independent variable of this research is APIP Ethical Codes (Integrity, Objectivity, Privacy, and Capability), and dependent variable is government performance of auditor. Regards to the result, therefore variable that APIP Ethical Codes simultaneously affect the government performance of auditor and partial that variable Objectivity affect the government performance of auditor, whereas variable Integrity, Privacy, and Capability rejected government performance of auditor.Keywords : Integrity, Objectivity, Privacy, Capability, And Performance Of Auditor

scholarly journals Allometric models for estimating Moringa oleifera leaflets area

2020 ◽  
Vol 44 ◽  
Author(s):  
Ana Paula Silva Macário ◽  
Rener Luciano de Souza Ferraz ◽  
Patrícia da Silva Costa ◽  
José Félix de Brito Neto ◽  
Alberto Soares de Melo ◽  
...  
Keyword(s):  
Regression Models ◽  
Moringa Oleifera ◽  
Future Research ◽  
State University ◽  
Linear Measurements ◽  
Bivariate Model ◽  
Allometric Models ◽  
Length Width ◽  
And Performance ◽  
Non Destructive

ABSTRACT Moringa oleifera is a species of great economic, social and environmental importance, being employed for multiple purposes. Thus, the objective of this study was to fit regression models for estimating leaflets area as non-destructive method from linear measurements of leaflets of M. oleifera seedlings. The study was carried out at the Center for Agrarian and Environmental Sciences of the Paraíba State University. Three hundred leaflets of M. oleifera were collected and measured to determine length “L” and width “W” and, subsequently, leaflets area was quantified through ImageJ® software. Using 200 leaflets, the univariate regression models were fitted, adopting length, width or the product of these dimensions “LW” and a bivariate model based on length and width as predictor variables of the observed leaflets area as dependent variable. The remaining 100 leaflets were used to evaluate the relationship between the observed leaflet area “OLA” and the estimated leaflets area “ELA”, based on Pearson’s correlation “r”; Willmott’s index of agreement “d” and index of confidence “c”; and root mean square error “RMSE”. It was found that allometric models can be used with high accuracy and performance to estimate the leaflets area of M. oleifera as non-destructive method, and recommended model is ELA = 0.035 + 0.720*LW. Future research is suggested for fittings of multivariate models to estimate the leaf area of M. oleifera from varying leaflet sizes, complete leaves, leaf fresh and dry weights, history of life and age of plants.

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