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作者:LI, WK
摘要:The asymptotic distribution of residual autocorrelations and a score statistic are derived for checking model adequacy for some Markov regression models for time series. These models are natural extensions of the popular generalized linear models to time series data. The score statistic appears to be somewhat easier to use in practice. Some empirical results are also obtained for the score statistic in some simple cases. A real example is given.
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作者:SCOTT, DW; WAND, MP
作者单位:Texas A&M University System; Texas A&M University College Station
摘要:The 'curse of dimensionality' has been interpreted as suggesting that kernel methods have limited applicability in more than several dimensions. In this note, qualitative and quantitative performance measures for multivariate density estimates are examined. Optimal pointwise and global window widths for mean absolute and mean squared errors are compared for multivariate data. One result is that the optimal pointwise absolute and squared error window widths are nearly equal for all dimensions. ...
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作者:LIN, DY
摘要:This paper addresses sequential testing in randomized clinical trials with multiple endpoints. Patients enter treatments serially and are subject to random loss to followup. The endpoints of interest may be time-to-event variables or other quantitative measurements. The proposed test statistic at a given look is a weighted sum of the linear rank statistics with respect to the marginal distributions of the multiple endpoints. The weights can be chosen to maximize asymptotic power against certai...
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作者:NAYAK, TK
摘要:We consider a superposition of an unknown number of independent homogeneous Poisson processes with unknown rates and suppose that when an event occurs, the component process in which it occurred can be identified. The number of component processes and their rates are to be estimated by observing the system for some time. In the general case, it is difficult to estimate all of the parameters but we derive the best unbiased estimators of some parametric functions. Inferences for the special case...