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作者：Henderson, R; Oman, P
作者单位：Lancaster University; Northumbria University
摘要：Unexplained heterogeneity in univariate survival data end association in multivariate survival can both be modelled by the inclusion of frailty effects. This paper investigates the consequences of ignoring frailty in analysis, fitting misspecified Cox proportional hazards models to the marginal distributions. Regression coefficients are biased towards 0 by an amount which depends in magnitude on the variability of the frailly terms and the form of frailty distribution. The bias is reduced when...
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作者：Lin, DY; Yip, PSF
作者单位：University of Washington; University of Washington Seattle; University of Hong Kong
摘要：We use a class of parametric counting process regression models that are commonly employed in the analysis of failure time data to formulate the subject-specific capture probabilities for removal and recapture studies conducted in continuous time. We estimate the regression parameters by modifying the conventional likelihood score function for left-truncated and right-censored data to accommodate an unknown population size and missing covariates on uncaptured subjects, and we subsequently esti...
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作者：Haslett, J
作者单位：Trinity College Dublin
摘要：A general. simple and intuitive derivation is provided for diagnostics associated with the deletion of arbitrary subsets for the linear model with general covariance structure. These are seen to be most simply expressed, even for the well-studied case of independent and identically distributed data, in terms of a residual known variously as the conditional residual, the deletion prediction residual and the cross-validation residual. Particularly simple specializations arise when the subsets ar...
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作者：Lee, SMS; Young, GA
作者单位：University of Cambridge; University of Hong Kong
摘要：A double-bootstrap confidence interval must usually be approximated by a Monte Carlo simulation, consisting of two nested levels of bootstrap sampling. We provide an analysis of the coverage accuracy of the interval which takes account of both the inherent bootstrap and Monte Carlo errors. The analysis shows that, by a suitable choice of the number of resamples drawn at the inner level of bootstrap sampling, we can reduce the order of coverage error. We consider also the effects of performing ...
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作者：Chen, MH; Ibrahim, JG; Yiannoutsos, C
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Worcester Polytechnic Institute
摘要：Bayesian selection of variables is often difficult to carry out because of the challenge in specifying prior distributions for the regression parameters for all possible models, specifying a prior distribution on the model space and computations. We address these three issues for the logistic regression model. For the first, we propose an informative prior distribution for variable selection. Several theoretical and computational properties of the prior are derived and illustrated with several...
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作者：Eguchi, S; Copas, J
作者单位：University of Warwick; Research Organization of Information & Systems (ROIS); Institute of Statistical Mathematics (ISM) - Japan
摘要：The local maximum likelihood estimate <(theta)over cap>(t) of a parameter in a statistical model f(x, theta) is defined by maximizing a weighted version of the likelihood function which gives more weight to observations in the neighbourhood of t. The paper studies the sense in which f(t, <(theta)over cap>(t)) is closer to the true distribution g(t) than the usual estimate f(t, <(theta)over cap>) is. Asymptotic results are presented for the case in which the model misspecification becomes vanis...
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作者：Gasser, T; Hall, P; Presnell, B
作者单位：Australian National University; University of Zurich
摘要：Motivated by the need to develop meaningful empirical approximations to a 'typical' data value, we introduce methods for density and mode estimation when data are in the form of random curves. Our approach is based on finite dimensional approximations via generalized Fourier expansions on an empirically chosen basis. The mode estimation problem is reduced to a problem of kernel-type multivariate estimation from vector data and is solved using a new recursive algorithm for finding the empirical...
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作者：Smith, M; Wong, CM; Kohn, R
作者单位：University of New South Wales Sydney; Monash University; Hong Kong University of Science & Technology
摘要：A Bayesian approach is presented for nonparametric estimation of an additive regression model with autocorrelated errors. Each of the potentially non-linear components is modelled as a regression spline using many knots, while the errors are modelled by a high order stationary autoregressive process parameterized in terms of its autocorrelations. The distribution of significant knots and partial autocorrelations is accounted for using subset selection. Our approach also allows the selection of...
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作者：Xia, YC
作者单位：University of Hong Kong
摘要：Bias-corrected confidence bands for general nonparametric regression models are considered. We use local polynomial fitting to construct the confidence bands and combine the cross-validation method and the plug-in method to select the bandwidths. Related asymptotic results are obtained. Our simulations show that confidence bands constructed by local polynomial fitting have much better coverage than those constructed by using the Nadaraya-Watson estimator. The results are also applicable to non...
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作者：Ramsay, JO
作者单位：McGill University
摘要：Many situations call for a smooth strictly monotone function f of arbitrary flexibility. The family of functions defined by the differential equation D(2)f = w Df, where w is an unconstrained coefficient function, comprises the strictly monotone twice differentiable functions. The solution to this equation is f = C-0 + C-1 D-1{exp(D(-1)w)}, where C-0 and C-1 are arbitrary constants and D-1 is the partial integration operator. A basis for expanding w is suggested that permits explicit integrati...
