Updating Schemes, Correlation Structure, Blocking and Parameterization for the Gibbs Sampler

Roberts, Gareth O.; Sahu, Sujit K.

doi:10.1111/1467-9868.00070

Cited by 356 publications

(280 citation statements)

References 23 publications

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“…Concurrent with the increased application of MCMC sampling schemes to non-Gaussian state space models, has been the revelation that substantial improvements in the simulation efficiency of MCMC schemes, in a variety of contexts, can sometimes be obtained though simple model reparameterisation. Relevant work includes Gelfand, Sahu and Carlin (1995), Roberts and Sahu (1997), Pitt and Shephard (1999) Bos and Shephard (2006). This paper contributes to the literature by examining the effect of particular types of reparameterisation in two specific non-Gaussian state space models.…”

Section: Introductionmentioning

confidence: 98%

Parameterisation and efficient MCMC estimation of non-Gaussian state space models

Strickland

Martin

Forbes

2008

Computational Statistics & Data Analysis

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The impact of parameterisation on the simulation efficiency of Bayesian Markov chain Monte Carlo (MCMC) algorithms for two nonGaussian state space models is examined. Specifically, focus is given to particular forms of the stochastic conditional duration (SCD) model and the stochastic volatility (SV) model, with four alternative parameterisations of each model considered. A controlled experiment using simulated data reveals that relationships exist between the simulation efficiency of the MCMC sampler, the magnitudes of the population parameters and the particular parameterisation of the state space model. Results of an empirical analysis of two separate transaction data sets for the SCD model, as well as equity and exchange rate data sets for the SV model, are also reported. Both the simulation and empirical results reveal that substantial gains in simulation efficiency can be obtained from simple reparameterisations of both types of non-Gaussian state space models.

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Section: Introductionmentioning

confidence: 98%

Parameterisation and efficient MCMC estimation of non-Gaussian state space models

Strickland

Martin

Forbes

2008

Computational Statistics & Data Analysis

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“…[17,37]). Joint updating of parameters is known to improve mixing in hierarchical models [28,29,33]. Along this line, Sorensen et al [37] suggested sampling the thresholds and the liabilities jointly to improve the mixing of thresholds.…”

Section: Discussionmentioning

confidence: 99%

A bivariate quantitative genetic model for a threshold trait and a survival trait

Damgaard¹,

Korsgaard²

2006

Genet. Sel. Evol.

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-Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.bivariate genetic model / survival trait / ordered categorical trait / Bayesian analysis

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“…The benefit of using a blocked sampler is that we only need one random draw to sample both the perspective indicator x i and the topic indicator z i , reducing the computational burden. Blocking a Gibbs sampler can also improve mixing of the MCMC chain, although this is not true in general (Roberts & Sahu 1997). The sampler has been implemented in C++/R and has been open sourced as an R package that can be found at https: //github.com/MansMeg/PerspectiveTopicModel.…”

Section: A Model Detailsmentioning

confidence: 99%

Voices from the far right: a text analysis of Swedish parliamentary debates

Magnusson¹,

Öhrvall²,

Barrling³

et al. 2018

Preprint

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In this paper we study the effects of a radical right party entering a national parliament, on the parliament discourse. We follow the classification developed by Meguid (2008) and use a probabilistic topic model approach to analyze the 300,000 speeches delivered in the Swedish parliament between 1994 and 2017. Our results indicate that immigration became a more prevalent topic in party leader debates when the Sweden Democrats entered the parliament in 2010. The other parties started to address immigration more, but still not to the extent that the Sweden Democrats did. In 2015, as Sweden faced a migration crisis, immigration became a more salient issue in the parliamentary debates. This could be seen as an external shock that forced the mainstream parties to put more emphasis on the topic of immigration. We conclude that the mainstream parties used a partly dismissive, partly adversarial strategy in their speeches when the SD entered the parliament. The migration crises in 2015 made them focus more on immigration and they thereby adopted a more adversarial strategy.

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Updating Schemes, Correlation Structure, Blocking and Parameterization for the Gibbs Sampler

Cited by 356 publications

References 23 publications

Parameterisation and efficient MCMC estimation of non-Gaussian state space models

Parameterisation and efficient MCMC estimation of non-Gaussian state space models

A bivariate quantitative genetic model for a threshold trait and a survival trait

Voices from the far right: a text analysis of Swedish parliamentary debates

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