type="main" xml:id="sjos12028-abs-0001" <title type="main">ABSTRACT</title>This paper considers inference for both spatial lattice data with possibly irregularly shaped sampling region and non-lattice data, by extending the recently proposed self-normalization (SN) approach from stationary time series to the spatial...

This paper is concerned with the inference of nonparametric mean function in a time series context. The commonly used kernel smoothing estimate is asymptotically normal and the traditional inference procedure then consistently estimates the asymptotic variance function and relies upon normal...

type="main" xml:id="jtsa12096-abs-0001"This article is concerned with confidence interval construction for functionals of the survival distribution for censored dependent data. We adopt the recently developed self-normalization approach (Shao, 2010), which does not involve consistent estimation...

In this article, we propose a new metric, the so-called martingale difference correlation, to measure the departure of conditional mean independence between a scalar response variable <italic>V</italic> and a vector predictor variable <italic>U</italic>. Our metric is a natural extension of distance correlation proposed by...

We propose a new method, to construct confidence intervals for spectral mean and related ratio statistics of a stationary process, that avoids direct estimation of their asymptotic variances. By introducing a bandwidth, a self-normalization procedure is adopted and the distribution of the new...