Journal of the Royal Statistical Society: Series B

最新文章

• Estimation of generalized linear latent variable models AI翻译
  作者：Huber, P; Ronchetti, E; Victoria-Feser, MP
  作者单位：University of Geneva
  摘要：Generalized linear latent variable models (GLLVMs), as defined by Bartholomew and Knott, enable modelling of relationships between manifest and latent variables. They extend structural equation modelling techniques, which are powerful tools in the social sciences. However, because of the complexity of the log-likelihood function of a GLLVM, an approximation such as numerical integration must be used for inference. This can limit drastically the number of variables in the model and can lead to ...
• Hypothesis testing in mixture regression models AI翻译
  作者：Zhu, HT; Zhang, HP
  作者单位：Yale University
  摘要：We establish asymptotic theory for both the maximum likelihood and the maximum modified likelihood estimators in mixture regression models. Moreover, under specific and reasonable conditions, we show that the optimal convergence rate of n(-1/4) for estimating the mixing distribution is achievable for both the maximum likelihood and the maximum modified likelihood estimators. We also derive the asymptotic distributions of two log-likelihood ratio test statistics for testing homogeneity and we p...
• A note on the adaptive control of false discovery rates AI翻译
  作者：Black, MA
  作者单位：University of Auckland
  摘要：The use of a fixed rejection region for multiple hypothesis testing has been shown to outperform standard fixed error rate approaches when applied to control of the false discovery rate. In this work it is demonstrated that, if the original step-up procedure of Benjamini and Hochberg is modified to exercise adaptive control of the false discovery rate, its performance is virtually identical to that of the fixed rejection region approach. In addition, the dependence of both methods on the propo...
• Semiparametric non-linear time series model selection AI翻译
  作者：Gao, JT; Tong, H
  作者单位：University of Western Australia; University of Hong Kong; University of London; London School Economics & Political Science
  摘要：Semiparametric time series regression is often used without checking its suitability, resulting in an unnecessarily complicated model. In practice, one may encounter computational difficulties caused by the curse of dimensionality. The paper suggests that to provide more precise predictions we need to choose the most significant regressors for both the parametric and the nonparametric time series components. We develop a novel cross-validation-based model selection procedure for the simultaneo...
• Estimating functions in indirect inference AI翻译
  作者：Heggland, K; Frigessi, A
  作者单位：University of Oslo
  摘要：There are models for which the evaluation of the likelihood is infeasible in practice. For these models the Metropolis-Hastings acceptance probability cannot be easily computed. This is the case, for instance, when only departure times from a G/G/1 queue are observed and inference on the arrival and service distributions are required. Indirect inference is a method to estimate a parameter theta in models whose likelihood function does not have an analytical closed form, but from which random s...
• A conditional approach for multivariate extreme values - Discussion on the paper by Heffernan and Tawn AI翻译
  作者：Smith, RL; Coles, S; Ferro, C; Butler, A; Anderson, M; Sahu, SK; Mardia, KV; Dupuis, DJ; Drees, H; Atkinson, AC; Beirlant, J; Goegebeur, Y; Boldi, MO; Davison, AC; Chatfield, C; Ledford, A; Peng, L; Qi, Y; Segers, J
  作者单位：University of North Carolina; University of North Carolina Chapel Hill
• Clustering objects on subsets of attributes - Discussion AI翻译
  作者：Hand, DJ; Glasbey, C; Husmeier, D; Gower, JC; van Houwelingen, HC; Bugrien, JB; Nason, G; Critchley, F; Hoff, PD; McLachlan, GJ; Bean, RW
  作者单位：Imperial College London; Open University - UK; Leiden University; Leiden University Medical Center (LUMC); Leiden University - Excl LUMC; University of Leeds; University of Bristol; University of Washington; University of Washington Seattle; University of Queensland
• Nonparametric inference about service time distribution from indirect measurements AI翻译
  作者：Hall, P; Park, J
  作者单位：Australian National University; University of North Carolina; University of North Carolina Chapel Hill
  摘要：In studies of properties of queues, for example in relation to Internet traffic, a subject that is of particular interest is the 'shape' of service time distribution. For example, we might wish to know whether the service time density is unimodal, suggesting that service time distribution is possibly homogeneous, or whether it is multimodal, indicating that there are two or more distinct customer populations. However, even in relatively controlled experiments we may not have access to explicit...
• Dicussion on the meeting on 'Statistical approaches to inverse problems AI翻译
  作者：Nason, G; Moulines, E; Robert, CP; Andrieu, C; Stoffelen, A; Paul, D; Abramovich, F; Aykroyd, RG; West, RM; Meng, S; Butucea, C; Cavalier, L; Davy, M; De Canditiis, D; Golubev, Y; Hoffman, RN; Khabie-Zeitoune, E; Munk, A; Ruymgaart, FH; Olhede, SC; Tsybakov, A; Wahba, G; Johnstone, IM; Kerkyacharian, G; Picard, D; Raimondo, M; Wolfe, PJ; Godsill, SJ; Ng, WJ; Haario, H; Laine, M; Lehtinen, M; Saksman, E; Tamminen, J; Cornford, D; Csató, L; Evans, DJ; Opper, M
  作者单位：University of Bristol
• Efficiency of generalized estimating equations for binary responses AI翻译
  作者：Rao Chaganty, N; Joe, H
  作者单位：Old Dominion University; University of British Columbia
  摘要：Using standard correlation bounds, we show that in generalized estimation equations (GEEs) the so-called 'working correlation matrix'R(alpha) for analysing binary data cannot in general be the true correlation matrix of the data. Methods for estimating the correlation param-eter in current GEE software for binary responses disregard these bounds. To show that the GEE applied on binary data has high efficiency, we use a multivariate binary model so that the covariance matrix from estimating equ...