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Tie the straps: Uniform bootstrap confidence bands for semiparametric additive models

Härdle, Wolfgang Karl; Ritov, Ya’acov; Wang, Weining - In: Journal of Multivariate Analysis 134 (2015) C, pp. 129-145

This study considers the theoretical bootstrap “coupling” techniques for nonparametric robust smoothers and quantile … regression, and we verify the bootstrap improvement. To handle the curse of dimensionality, a variant of “coupling” bootstrap … bootstrap method can be used in many situations such as constructing confidence intervals and bands. We demonstrate the …

Persistent link: https://www.econbiz.de/10011189579

Bootstrap testing for discontinuities under long-range dependence

Beran, Jan; Shumeyko, Yevgen - In: Journal of Multivariate Analysis 105 (2012) 1, pp. 322-347

We consider testing for discontinuities in a trend function when the residual process exhibits long memory. Using a wavelet decomposition of the estimated trend function into a low-resolution and a high-resolution component, a test statistic is proposed based on blockwise resampling of estimated...

Persistent link: https://www.econbiz.de/10010572292

On variance estimation in a negative binomial time series regression model

Wu, Rongning - In: Journal of Multivariate Analysis 112 (2012) C, pp. 145-155

model estimator. We propose two types of estimators using kernel-based and subsampling methods, and establish their …

Persistent link: https://www.econbiz.de/10010594229

Law of log determinant of sample covariance matrix and optimal estimation of differential entropy for high-dimensional Gaussian distributions

Cai, T. Tony; Liang, Tengyuan; Zhou, Harrison H. - In: Journal of Multivariate Analysis 137 (2015) C, pp. 161-172

Differential entropy and log determinant of the covariance matrix of a multivariate Gaussian distribution have many applications in coding, communications, signal processing and statistical inference. In this paper we consider in the high-dimensional setting optimal estimation of the...

Persistent link: https://www.econbiz.de/10011263462

Covariance matrices associated to general moments of a random vector

Lv, Songjun - In: Journal of Multivariate Analysis 134 (2015) C, pp. 61-70

It turns out that there exist general covariance matrices associated not only to a random vector itself but also to its general moments. In this paper we introduce and characterize general covariance matrices of a random vector that are associated to some important general moments, which are...

Persistent link: https://www.econbiz.de/10011189578

Minimax covariance estimation using commutator subgroup of lower triangular matrices

Tsukuma, Hisayuki - In: Journal of Multivariate Analysis 124 (2014) C, pp. 333-344

This paper deals with the problem of estimating the normal covariance matrix relative to the Stein loss. The main interest concerns a new class of estimators which are invariant under a commutator subgroup of lower triangular matrices. The minimaxity of a James–Stein type invariant estimator...

Persistent link: https://www.econbiz.de/10010737755

Hypothesis testing for high-dimensional covariance matrices

Li, Weiming; Qin, Yingli - In: Journal of Multivariate Analysis 128 (2014) C, pp. 108-119

This paper discusses the problem of testing for high-dimensional covariance matrices. Tests for an identity matrix and for the equality of two covariance matrices are considered when the data dimension and the sample size are both large. Most importantly, the dimension can be much larger than...

Persistent link: https://www.econbiz.de/10010776643

A new test for the proportionality of two large-dimensional covariance matrices

Liu, Baisen; Xu, Lin; Zheng, Shurong; Tian, Guo-Liang - In: Journal of Multivariate Analysis 131 (2014) C, pp. 293-308

Let X1,…,Xn1+1∼iidNp(μ1,Σ1) and Y1,…,Yn2+1∼iidNp(μ2,Σ2) be two independent random samples, where pn2. In this article, we propose a new test for the proportionality of two large p×p covariance matrices Σ1 and Σ2. By applying modern random matrix theory, we establish the asymptotic...

Persistent link: https://www.econbiz.de/10011041913

Minimax optimal estimation of general bandable covariance matrices

Xue, Lingzhou; Zou, Hui - In: Journal of Multivariate Analysis 116 (2013) C, pp. 45-51

Cai et al. (2010) [4] have studied the minimax optimal estimation of a collection of large bandable covariance matrices whose off-diagonal entries decay to zero at a polynomial rate. They have shown that the minimax optimal procedures are fundamentally different under Frobenius and spectral...

Persistent link: https://www.econbiz.de/10011041948

Asymptotic expansion for distribution of the trace of a covariance matrix under a two-step monotone incomplete sample

Tsukada, Shin-ichi - In: Journal of Multivariate Analysis 129 (2014) C, pp. 206-219

The covariance matrix is embedded in several statistics (such as the trace and general variance) of multivariate statistical analysis. We investigate the trace of the covariance matrix in the context of a two-step monotone incomplete sample drawn from Np+q(μ,Σ), a multivariate normal...

Persistent link: https://www.econbiz.de/10011041982