论文检索

时间扭曲函数型回归AI 解读

A characteristic feature of functional data is the presence of phase variability in addition to amplitude variability. Existing functional regression methods do not handle time variability in an explicit and efficient way. In this paper we introduce a functional regression method that incorporates time warping as an intrinsic part of the model. The method achieves good predictive power in a parsimonious way and allows unified statistical inference about phase and amplitude…

利用中位数与球面主成分进行稳健函数估计AI 解读

We present robust estimators for the mean and the principal components of a stochastic process in . Robustness and asymptotic properties of the estimators are studied theoretically, by simulation and by example. It is shown that the proposed estimators are generally more robust to outliers than the commonly used sample mean and principal components, although their properties depend on the spacings of the eigenvalues of the covariance function. Copyright 2008, Oxford…

修订与更正：一般扭曲函数估计式的先前来源AI 解读

It has been brought to our attention that the implicit expression (6) for the estimator with general warping function had been derived earlier by B. Ronn, in an unpublished technical report of the Royal Veterinary and Agricultural University, Frederiksberg. However, the actual implementation and computation of the estimators are very different in our paper from in the technical report. Copyright 2006, Oxford University Press.