Journal of the Royal Statistical Society: Series B

最新文章

• Estimation of direct effects for survival data by using the Aalen additive hazards model AI翻译
  作者：Martinussen, Torben; Vansteelandt, Stijn; Gerster, Mette; Hjelmborg, Jacob von Bornemann
  作者单位：University of Copenhagen; Ghent University; University of London; London School of Hygiene & Tropical Medicine; University of Southern Denmark
  摘要：We extend the definition of the controlled direct effect of a point exposure on a survival outcome, other than through some given, time-fixed intermediate variable, to the additive hazard scale. We propose two-stage estimators for this effect when the exposure is dichotomous and randomly assigned and when the association between the intermediate variable and the survival outcome is confounded only by measured factors, which may themselves be affected by the exposure. The first stage of the est...
• Robustness of design in dose-response studies AI翻译
  作者：Li, Pengfei; Wiens, Douglas P.
  作者单位：University of Alberta
  摘要：We construct experimental designs for dose-response studies. The designs are robust against possibly misspecified link functions; for this they minimize the maximum mean-squared error of the estimated dose required to attain a response in 100p% of the target population. Here p might be one particular value-p=0.5 corresponds to ED50-estimation-or it might range over an interval of values of interest. The maximum of the mean-squared error is evaluated over a Kolmogorov neighbourhood of the fitte...
• Modelling non-homogeneous Poisson processes with almost periodic intensity functions AI翻译
  作者：Shao, Nan; Lii, Keh-Shin
  作者单位：University of California System; University of California Riverside
  摘要：We propose a model for the analysis of non-stationary point processes with almost periodic rate of occurrence. The model deals with the arrivals of events which are unequally spaced and show a pattern of periodicity or almost periodicity, such as stock transactions and earthquakes. We model the rate of occurrence of a non-homogeneous Poisson process as the sum of sinusoidal functions plus a baseline. Consistent estimates of frequencies, phases and amplitudes which form the sinusoidal functions...
• On the use of non-local prior densities in Bayesian hypothesis tests AI翻译
  作者：Johnson, Valen E.; Rossell, David
  作者单位：University of Texas System; UTMD Anderson Cancer Center; Barcelona Institute of Science & Technology; Institute for Research in Biomedicine - IRB Barcelona
  摘要：We examine philosophical problems and sampling deficiencies that are associated with current Bayesian hypothesis testing methodology, paying particular attention to objective Bayes methodology. Because the prior densities that are used to define alternative hypotheses in many Bayesian tests assign non-negligible probability to regions of the parameter space that are consistent with null hypotheses, resulting tests provide exponential accumulation of evidence in favour of true alternative hypot...
• Signed directed acyclic graphs for causal inference AI翻译
  作者：VanderWeele, Tyler J.; Robins, James M.
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health
  摘要：Formal rules governing signed edges on causal directed acyclic graphs are described and it is shown how these rules can be useful in reasoning about causality. Specifically, the notions of a monotonic effect, a weak monotonic effect and a signed edge are introduced. Results are developed relating these monotonic effects and signed edges to the sign of the causal effect of an intervention in the presence of intermediate variables. The incorporation of signed edges in the directed acyclic graph ...
• Maximum likelihood estimation of a multi-dimensional log-concave density AI翻译
  作者：Cule, Madeleine; Samworth, Richard; Stewart, Michael
  作者单位：University of Cambridge; University of Sydney
  摘要：Let X-1,...,X-n be independent and identically distributed random vectors with a (Lebesgue) density f. We first prove that, with probability 1, there is a unique log-concave maximum likelihood estimator f(n) of f. The use of this estimator is attractive because, unlike kernel density estimation, the method is fully automatic, with no smoothing parameters to choose. Although the existence proof is non-constructive, we can reformulate the issue of computing f(n) in terms of a non-differentiable ...
• Default priors for Bayesian and frequentist inference AI翻译
  作者：Fraser, D. A. S.; Reid, N.; Marras, E.; Yi, G. Y.
  作者单位：University of Toronto; University of Waterloo
  摘要：We investigate the choice of default priors for use with likelihood for Bayesian and frequentist inference. Such a prior is a density or relative density that weights an observed likelihood function, leading to the elimination of parameters that are not of interest and then a density-type assessment for a parameter of interest. For independent responses from a continuous model, we develop a prior for the full parameter that is closely linked to the original Bayes approach and provides an exten...
• Particle Markov chain Monte Carlo methods AI翻译
  作者：Andrieu, Christophe; Doucet, Arnaud; Holenstein, Roman
  作者单位：University of British Columbia; University of Bristol; Research Organization of Information & Systems (ROIS); Institute of Statistical Mathematics (ISM) - Japan
  摘要：Markov chain Monte Carlo and sequential Monte Carlo methods have emerged as the two main tools to sample from high dimensional probability distributions. Although asymptotic convergence of Markov chain Monte Carlo algorithms is ensured under weak assumptions, the performance of these algorithms is unreliable when the proposal distributions that are used to explore the space are poorly chosen and/or if highly correlated variables are updated independently. We show here how it is possible to bui...
• Random-weight particle filtering of continuous time processes AI翻译
  作者：Fearnhead, Paul; Papaspiliopoulos, Omiros; Roberts, Gareth O.; Stuart, Andrew
  作者单位：Pompeu Fabra University; Lancaster University; University of Warwick
  摘要：It is possible to implement importance sampling, and particle filter algorithms, where the importance sampling weight is random. Such random-weight algorithms have been shown to be efficient for inference for a class of diffusion models, as they enable inference without any (time discretization) approximation of the underlying diffusion model. One difficulty of implementing such random-weight algorithms is the requirement to have weights that are positive with probability 1. We show how Wald's...
• Explicit estimating equations for semiparametric generalized linear latent variable models AI翻译
  作者：Ma, Yanyuan; Genton, Marc G.
  作者单位：Texas A&M University System; Texas A&M University College Station
  摘要：We study generalized linear latent variable models without requiring a distributional assumption of the latent variables. Using a geometric approach, we derive consistent semiparametric estimators. We demonstrate that these models have a property which is similar to that of a sufficient complete statistic, which enables us to simplify the estimating procedure and explicitly to formulate the semiparametric estimating equations. We further show that the explicit estimators have the usual root n ...