## SEARCH

#### Institution

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- Technische Universität Dortmund 26 (%)
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#### Author

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- Maronna, Ricardo 30 (%)
- Krämer, Walter 24 (%)
- Kleiber, Christian 22 (%)
- RicardoMaronna Ricardo Maronna 21 (%)
- Nadarajah, Saralees 19 (%)

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- Probability Theory and Stochastic Processes 1716 (%)
- Statistics [x] 1716 (%)
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## Local expectations of the population spectral distribution of a high-dimensional covariance matrix

### Statistical Papers (2014-05-01) 55: 563-573 , May 01, 2014

This paper discusses the relationship between the population spectral distribution and the limit of the empirical spectral distribution in high-dimensional situations. When the support of the limiting spectral distribution is split into several intervals, the population one gains a meaningful division, and general functional expectations of each part from the division, referred as local expectations, can be formulated as contour integrals around these intervals. Basing on these knowledge we present consistent estimators of the local expectations and prove a central limit theorem for them. The results are then used to analyze an estimator of the population spectral distribution in recent literature.

## Goodness-of-fit tests for semiparametric and parametric hypotheses based on the probability weighted empirical characteristic function

### Statistical Papers (2016-12-01) 57: 957-976 , December 01, 2016

We investigate the finite-sample properties of certain procedures which employ the novel notion of the probability weighted empirical characteristic function. The procedures considered are: (1) Testing for symmetry in regression, (2) Testing for multivariate normality with independent observations, and (3) Testing for multivariate normality of random effects in mixed models. Along with the new tests alternative methods based on the ordinary empirical characteristic function as well as other more well known procedures are implemented for the purpose of comparison.

## On two simple and effective procedures for high dimensional classification of general populations

### Statistical Papers (2016-04-01) 57: 381-405 , April 01, 2016

In this paper, we generalize two criteria, the determinant-based and trace-based criteria proposed by Saranadasa (J Multivar Anal 46:154–174, 1993), to general populations for high dimensional classification. These two criteria compare some distances between a new observation and several different known groups. The determinant-based criterion performs well for correlated variables by integrating the covariance structure and is competitive to many other existing rules. The criterion however requires the measurement dimension be smaller than the sample size. The trace-based criterion, in contrast, is an independence rule and effective in the “large dimension-small sample size” scenario. An appealing property of these two criteria is that their implementation is straightforward and there is no need for preliminary variable selection or use of turning parameters. Their asymptotic misclassification probabilities are derived using the theory of large dimensional random matrices. Their competitive performances are illustrated by intensive Monte Carlo experiments and a real data analysis.

## Erratum to: Multivariate normal distribution approaches for dependently truncated data

### Statistical Papers (2014-11-01) 55: 1233-1236 , November 01, 2014

## Wavelet estimation of the memory parameter for long range dependent random fields

### Statistical Papers (2014-11-01) 55: 1145-1158 , November 01, 2014

In this paper we study the estimation of the spatial long memory parameter for stationary long range dependent random fields using wavelet methods. We first show the relation between the wavelet coefficients of the random fields and its long memory parameter. Based on this relation, we construct a log-regression wavelet estimator of the long memory parameter. Under some mild regularity assumptions, the asymptotic properties of the estimators are investigated. Finally, a small simulation study illustrates the method.

## A note on D-optimal designs for models with and without an intercept

### Statistical Papers (2005-07-01) 46: 451-458 , July 01, 2005

In this paper we give a sufficient condition under which the*D*-optimal design for a regression model without an intercept can be obtained from the*D*-optimal design for the corresponding model with an intercept by simply removing the origin from its support points. Examples are given to demonstrate the applications of the results.

## A note on the mean past and the mean residual life of a (n − k + 1)-out-of-n system under multi monitoring

### Statistical Papers (2010-06-01) 51: 409-419 , June 01, 2010

In the study of the reliability of technical systems, *k*-out-of-*n* systems play an important role. In the present paper, we consider a (*n* − *k* + 1)-*out*-of-*n* system consisting of *n* identical components such that the lifetimes of components are independent and have a common distribution function *F*. It is assumed that the number of monitoring is *l* and the total number of failures of the components at time *t*_{i} is *m*_{i}, *i* = 1, . . . , *l* − 1. Also at time *t*_{l}(*t*_{1} < . . . < *t*_{l}) the system have failed or the system is still working. Under these conditions, the mean past lifetime, the mean residual lifetime of system and their properties are investigated.

## S. J. Morrison: Statistics for Engineers: an introduction

### Statistical Papers (2012-02-01) 53: 245-246 , February 01, 2012

## Small sample properties of asymptotically equivalent tests for autoregressive conditional heteroskedasticity

### Statistical Papers (1989-12-01) 30: 105-131 , December 01, 1989

Models that allow for autoregressive conditional heteroskedasticity (ARCH) in the error process have recently found widespread application. The purpose of this paper is to evaluate, through Monte Carlo analysis, the small sample properties of an exact Lagrange multiplier test for the presence of ARCH, and to compare the power of this test with that of an asymptotically equivalent TR^{2} version. The comparison involves first-and higher-order variants of these processes. The results indicate substantial power differentials in favor of the exact LM test, by up to 15% for sample sizes smaller than 100.