Semiparametric Bayesian analysis of nonlinear reproductive dispersion mixed models for longitudinal data

Tang, Niansheng; Zhao, Yuanying

doi:10.1016/j.jmva.2012.09.005

Cited by 10 publications

(7 citation statements)

References 37 publications

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“…In view of the designated research aim, this research adopts a longitudinal study as the core of the methodology. A longitudinal study is a correlational research study that involves repeated observations of the same variables over long periods of time [23]. It has several advantages, e.g.…”

Section: Methodsmentioning

confidence: 99%

Construction waste management policies and their effectiveness in Hong Kong: A longitudinal review

Tam

2013

Renewable and Sustainable Energy Reviews

200

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Solid waste arisen from construction activities is grave concern in many economies. Given its negative impacts to the natural environment as a public good, construction waste is often heavily regulated by authorities. Hong Kong is no exception to this; over the past decades, a series of construction waste management (CWM) policies including regulations, codes, and initiatives have been introduced by the Government and her executive arms. It comes to an opportune time to retrospectively examine the effectiveness of these policies with a view to providing insights for further improvement. The aim of this paper is thus to examine CWM policies and their effectiveness in Hong Kong by conducting a longitudinal study. The evaluation of the policy effectiveness is derived by triangulating empirical data collected from various sources including Hong Kong Census and Statistics Department, Civil Engineering and Development Department, Environment Protection Department, and Hong Kong Construction Association with the qualitative data gleaned from interviews and case studies in construction sites, waste sorting facilities, and landfills. It is found that Hong Kong is actively trying new CWM policies based on latest waste management philosophies available (e.g. reduce, reuse, and recycle principle, and polluter pays principle). These policies have formed an interlocking, and relatively effective policy framework for CWM in Hong Kong. However, new initiatives are desired if aiming to change the gloomy situation since 2006 when the construction waste disposal charging scheme was effectively implemented. This research provides insightful understanding of CWM policies and their effectiveness, which is often concerned policies makers, researchers, and the like.

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Section: Methodsmentioning

confidence: 99%

Construction waste management policies and their effectiveness in Hong Kong: A longitudinal review

Tam

2013

Renewable and Sustainable Energy Reviews

200

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“…Gibbs sampler procedure. Following Geyer[22], these joint Bayesian estimates and sample covariance matrices are consistent with their corresponding posterior expectations and posterior covariance matrices. Similar to Kuo and Mallick[17] and Zhao et al[18], the promising subsets of explanatory variables can be identified by high posterior probabilities of IV.…”

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confidence: 59%

“…The MH algorithm [20,21] is one of the most effective ways to generate samples from those corresponding conditional distributions with the help of proposal distributions. Similar to Tang and Zhao [22] and Zhao and Tang [23], we choose the following normal distribution…”

Section: A Conditional Distributionsmentioning

confidence: 99%

Bayesian Subset Selection for Inverse Gauss Regression Models

Zhao¹,

Xu²,

Jin³

et al. 2018

Proceedings of the 2018 2nd International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2018)

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“…erefore, we can obtain the standard errors by the diagonal elements of the sample covariance matrices. e partial posterior predictive (PPP) p-value proposed by Bayarri and Berger [23] is a goodness-of-fit statistic to investigate the plausibility of the posited model in Bayesian statistical framework; see more details in Lee and Tang [24], Tang and Zhao [25]. Similar to Lee and Tang [24] and Tang and Zhao [25], we can define the PPP p-value for our considered model as…”

Section: Bayesian Estimates and Goodness-of-fit Statisticmentioning

confidence: 99%

Bayesian Adaptive Lasso for Regression Models with Nonignorable Missing Responses

Zhao

Duan

2022

Journal of Mathematics

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The main purpose of this article is to develop a Bayesian adaptive lasso procedure for analyzing linear regression models with nonignorable missing responses, in which the missingness mechanism is specified by a logistic regression model. A sampling procedure combining the Gibbs sampler and Metropolis-Hastings algorithm is employed to obtain the Bayesian estimates of the regression coefficients, shrinkage coefficients, missingness mechanism models parameters, and their standard errors. We extend the partial posterior predictive p value for goodness-of-fit statistic to investigate the plausibility of the posited model. Finally, several simulation studies and the air pollution data example are undertaken to demonstrate the newly developed methodologies.

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Semiparametric Bayesian analysis of nonlinear reproductive dispersion mixed models for longitudinal data

Cited by 10 publications

References 37 publications

Construction waste management policies and their effectiveness in Hong Kong: A longitudinal review

Construction waste management policies and their effectiveness in Hong Kong: A longitudinal review

Bayesian Subset Selection for Inverse Gauss Regression Models

Bayesian Adaptive Lasso for Regression Models with Nonignorable Missing Responses

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