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作者：RICE, JA; ROSENBLATT, M
摘要：This paper discusses a least-squares procedure and the use of the periodogram for isolating a discrete harmonic of a time series. It is shown that the usual asymptotics on estimation of frequency, amplitude and phase of such a harmonic have to be used with great caution from a moderate sample perspective. Computational issues are discussed and some illustrations are provided. Bolt and Brillinger (1979) make use of these asymptotic results.
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作者：YOUNG, GA
摘要：Smoothed bootstrap estimation of the sampling standard deviation of the variance-stabilized correlation coefficient is reconsidered. An approximation to the mean squared error of the bootstrap estimator is obtained and an empirical procedure for choosing the degree of smoothing in the bootstrap estimation is presented. Performance of the procedure is examined in a simulation study.
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作者：BRESLOW, NE; CAIN, KC
摘要：Samples of diseased cases and nondiseased controls are drawn at random from the population at risk. After classification according to the exposure of interest, subsamples of cases and controls are selected for purposes of covariable ascertainment. A modification of the usual logistic regression analysis yields consistent estimates of covariable adjusted relative risks and their standard errors. By balancing the numbers of exposed and nonexposed for whom covariable information is ascertained wi...
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作者：SRIVASTAVA, MS; KEEN, KJ
摘要：A noniterative method for estimating the interclass correlation coefficient is derived from the technique of weighted sums of squares. The asymptotic variance of this estimator is derived under the assumption of normality. Through extensive Monte Carlo simulations, the sample variance of this estimator is found not to differ greatly from that of the maximum likelihood estimator.
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作者：AHN, SK
摘要：The asymptotic distribution is derived for residual autocovariances in the multivariate autoregressive model with structured parameterization, a form often employed in multivariate time series modelling to achieve parsimony. It is shown that a similar result for the asymptotic distribution of a portmanteau statistic for the usual full-rank autoregressive-moving average model can be extended to the autoregressive model with structured parameterization.
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作者：GOULD, A; LAWLESS, JF
摘要：The effect on estimation of regression coefficients in linear location-scale models is investigated when the error distribution is misspecified. It is shown that the maximum likelihood estimator under the incorrect model is still consistent. Its asymptotic efficiency relative to that of the maximum likelihood estimator based on the correct model is obtained and the estimation of asymptotic variances for the regression coefficient estimators is addressed.
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作者：BUCKLEY, MJ; EAGLESON, GK; SILVERMAN, BW
作者单位：University of Bath
摘要：A wide class of estimators of the residual variance in nonparametric regression is considered, namely those that are quadratic in the data, unbiased for linear regression, and always nonnegative. The minimax mean squared error estimator over a natural class of regression functions is derived. This optimal estimator has an interesting structure and is closely related to a minimax estimator of the regression curve itself.
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作者：FRANKE, J
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作者：HOSOYA, Y
摘要：The paper presents general second-order approximate formulae for the Fisher information of asymptotically normal statistics, and applies the formulae to a stationary time-series model as well as to an econometric simultaneous equation model. Also the second-order conditional information is evaluated for the exponential family and the location family. Conditioned on a second-order ancillary statistic, the second-order information loss of the maximum likelihood estimate is shown to be recovered.
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作者：BERMAN, M
摘要：A theorem of Jacobi (1841), which shows how the ordinary least-squares estimator from a linear regression can be represented as the weighted sum of ''elementary'' estimators of the parameters, is extended to the generalized least-squares estimator. The generalization is applied to a problem in microwave engineering.
