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• Optimal discrimination designs for multifactor experiments (vol 25, pg 1161, 1997) AI翻译
  作者：Dette, H; Röder, I
  作者单位：Ruhr University Bochum; Ruhr University Bochum; Leipzig University
• New goodness-of-fit tests and their application to nonparametric confidence sets AI翻译
  作者：Dümbgen, L
  作者单位：Ruprecht Karls University Heidelberg; University of Lubeck
  摘要：Suppose one observes a process V on the unit interval, where dV = f(o)+ dW with an unknown parameter f(o) epsilon L-1[0, 1] and standard Brownian motion W. We propose a particular test of one-point hypotheses about f(o) which is based on suitably standardized increments of V. This test is shown to have desirable consistency properties if, for instance, f(o) is restricted to various Holder classes of functions. The test is mimicked in the context of nonparametric density estimation, nonparametr...
• Limiting distributions of maximum likelihood estimators for unstable autoregressive moving-average time series with general autoregressive heteroscedastic errors AI翻译
  作者：Ling, SQ; Li, WK
  作者单位：University of Hong Kong
  摘要：This paper investigates the maximum likelihood estimator (MLE) for unstable autoregressive moving-average (ARMA) time series with the noise sequence satisfying a general autoregressive heteroscedastic (GARCH) process. Under some mild conditions, it is shown that the MLE satisfying the likelihood equation exists and is consistent. The limiting distribution of the RILE is derived in a unified manner for all types of characteristic roots on or outside the unit circle and is expressed as a functio...
• Asymptotic nonequivalence of nonparametric experiments when the smoothness index is 1/2 AI翻译
  作者：Brown, LD; Zhang, CH
  作者单位：University of Pennsylvania; Rutgers University System; Rutgers University New Brunswick
  摘要：An example is provided to show that the natural asymptotic equivalence does not hold between any pairs of three nonparametric experiments: density problem, white noise with drift and nonparametric regression, when the smoothness index of the unknown nonparametric function class is 1/2.
• Log-density estimation in linear inverse problems AI翻译
  作者：Koo, JY; Chung, HY
  作者单位：Hallym University
  摘要：We estimate a probability density function p which is related by a linear operator K to a density function q in sequences of regular exponential families based on a random sample from q. In this paper deconvolution and positron emission tomography are considered. The logarithm of the density Function is approximated by basis functions consisting of singular functions of K. While direct maximum likelihood (or minimum Kullback-Leibler) density estimation in exponential families selects the param...
• Sieve bootstrap for smoothing in nonstationary time series AI翻译
  作者：Bühlmann, P
  作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
  摘要：We propose a sieve bootstrap procedure for time series with a deterministic trend. The sieve for constructing the bootstrap is based on nonparametric trend estimation and autoregressive approximation for some noise process. The bootstrap scheme itself does i.i.d, resampling of estimated innovations from fitted autoregressive models. We show the validity and indicate second-order correctness of such sieve bootstrap approximations for the limiting distribution of nonparametric linear smoothers. ...
• Analysis of oldest-old mortality:: Lifetables revisited AI翻译
  作者：Wang, JL; Müller, HG; Capra, WB
  作者单位：University of California System; University of California Davis
  摘要：This paper provides a data analysis and some methodological advances which contribute to an ongoing scientific debate about the patterns of aging. One of the problems we address is how to estimate a hazard function when only aggregated information on the lifetimes in the form of a lifetable is available. This problem affects the estimation of oldest-old mortality which in turn plays an important role in the quantification of biological lifespan and longevity. We illustrate these issues with an...