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作者：Ni, LQ; Cook, RD; Tsai, CL
作者单位：State University System of Florida; University of Central Florida; University of Minnesota System; University of Minnesota Twin Cities; University of California System; University of California Davis
摘要：We employ Lasso shrinkage within the context of sufficient dimension reduction to obtain a shrinkage sliced inverse regression estimator, which provides easier interpretations and better prediction accuracy without assuming a parametric model. The shrinkage sliced inverse regression approach can be employed for both single-index and multiple-index models. Simulation studies suggest that the new estimator performs well when its tuning parameter is selected by either the Bayesian information cri...
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作者：Sweeting, TJ
作者单位：University of London; University College London
摘要：Probability matching priors are priors for which the posterior probabilities of certain specified sets are exactly or approximately equal to their coverage probabilities. These priors arise as solutions of partial differential equations that may be difficult to solve, either analytically or numerically. Recently Levine & Casella (2003) presented an algorithm for the implementation of probability matching priors for an interest parameter in the presence of a single nuisance parameter. In this p...
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作者：Crainiceanu, C; Ruppert, D; Claeskens, G; Wand, MP
作者单位：Johns Hopkins University; Cornell University; KU Leuven; University of New South Wales Sydney
摘要：Penalised-spline-based additive models allow a simple mixed model representation where the variance components control departures from linear models. The smoothing parameter is the ratio of the random-coefficient and error variances and tests for linear regression reduce to tests for zero random-coefficient variances. We propose exact likelihood and restricted likelihood ratio tests for testing polynomial regression versus a general alternative modelled by penalised splines. Their spectral dec...
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作者：Chen, KN; Jin, ZZ
作者单位：Hong Kong University of Science & Technology; Columbia University
摘要：This paper proposes a classical weighted least squares type of local polynomial smoothing for the analysis of clustered data, with the key idea of using generalised inverses of correlation matrices. The estimator has a simple closed-form expression. Simplicity is achieved also for nonparametric generalised linear models with arbitrary link function via a transformation. Our approach can be characterised by 'local observations with local variances', which yields intuitively correct results in t...
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作者：Ho, YHS; Lee, SMS
作者单位：University of Hong Kong
摘要：Beran & Hall's (1993) simple linear interpolation provides a very convenient approach for constructing nonparametric confidence intervals for population quantiles based on a random sample of size n. We show that the coverage error of the interpolated interval, which is of order O(n(-1)), can be improved upon by calibrating the nominal coverage level. Three distinct methods of calibration are considered. The analytical and Monte Carlo methods succeed in reducing the order of coverage error to O...
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作者：Yang, S; Prentice, R
作者单位：National Institutes of Health (NIH) - USA; NIH National Heart Lung & Blood Institute (NHLBI); Fred Hutchinson Cancer Center
摘要：Standard approaches to semiparametric modelling of two-sample survival data are not appropriate when the two survival curves cross. We introduce a two-sample model that accommodates crossing survival curves. The two scalar parameters of the model have the interpretations of being the short-term and long-term hazard ratios respectively. The time-varying hazard ratio is expressed semiparametrically by the two scalar parameters and an unspecified baseline distribution. The new model includes the ...
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作者：Hall, P; Qiu, PH
作者单位：Australian National University; University of Minnesota System; University of Minnesota Twin Cities
摘要：If Fourier series are used as the basis for inference in deconvolution problems, the effects of the errors factorise out in a way that is easily exploited empirically. This property is the consequence of elementary addition formulae for sine and cosine functions, and is not readily available when one is using methods based on other orthogonal series or on continuous Fourier transforms. It allows relatively simple estimators to be constructed, founded on the addition of finite series rather tha...
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作者：Brown, BM; Wang, YG
作者单位：National University of Singapore
摘要：A 'pseudo-Bayesian' interpretation of standard errors yields a natural induced smoothing of statistical estimating functions. When applied to rank estimation, the lack of smoothness which prevents standard error estimation is remedied. Efficiency and robustness are preserved, while the smoothed estimation has excellent computational properties. In particular, convergence of the iterative equation for standard error is fast, and standard error calculation becomes asymptotically a one-step proce...
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作者：Hwang, WH; Huggins, R
作者单位：Feng Chia University; La Trobe University
摘要：Part of the folklore of capture-recapture experiments is that ignoring heterogeneity of capture probabilities results in a downward bias. This has been based on experience and simulation studies but is often interpreted as being due to individuals with lower capture probabilities. Here estimating equation arguments are used to show that the effect on Horvitz-Thompson-type estimators of ignoring heterogeneity in capture-recapture experiments is to introduce a downward bias. The arguments are ex...
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作者：Schennach, SM
作者单位：University of Chicago
摘要：While empirical likelihood has been shown to exhibit many of the properties of conventional parametric likelihoods, a formal probabilistic interpretation has so far been lacking. We show that a likelihood function very closely related to empirical likelihood naturally arises from a nonparametric Bayesian procedure which places a type of noninformative prior on the space of distributions. This prior gives preference to distributions having a small support and, among those sharing the same suppo...
