Recursive formulae for the average efficiency factor in block and row-column designs

Interchange algorithms are widely used to construct efficient block and row-column designs. We provide simple recursive formulae for updating this average efficiency factor, so that it is no longer computationally expensive to calculate it after each possible interchange.     

Some methods for constructing C-designs

Block designs having a property described by Caliński (1971) and Saha (1976), referred to as C-property, are further considered. A necessary and sufficient condition for a block design to have the C-property is given by Saha (1976) and another by Ceranka and Koz?owska (1983). In this paper some methods for constructing such block designs are presented.     

恢复计算机失落数据在编辑中的应用

在编辑工作中 ,需要在计算机和网上工作 ,往往容易误删除计算机里有用的文件 ,网上病毒容易破坏文件 ,造成文件丢失 ,本文对恢复这些文件的技术进行了讨论 ,在许多软件中 ,FinalDate应用简便、功能强大 ,是这些软件的首选     

关于块复合矩阵的块特征值

本文讨论了块复合矩阵之块特征值的若干性质,同时给出了某些块复合矩阵之块特征值的包含域。本文的结果推广和改进了[1]～[3]的相应结论。     

Automatic Block-Length Selection for the Dependent Bootstrap

We review the different block bootstrap methods for time series, and present them in a unified framework. We then revisit a recent result of Lahiri [Lahiri, S. N. (1999b). Theoretical comparisons of block bootstrap methods, Ann. Statist. 27:386-404] comparing the different methods and give a corrected bound on their asymptotic relative efficiency; we also introduce a new notion of finite-sample “attainable” relative efficiency. Finally, based on the notion of spectral estimation via the flat-top lag-windows of Politis and Romano [Politis, D. N., Romano, J. P. (1995). Bias-corrected nonparametric spectral estimation. J. Time Series Anal. 16:67-103], we propose practically useful estimators of the optimal block size for the aforementioned block bootstrap methods. Our estimators are characterized by the fastest possible rate of convergence which is adaptive on the strength of the correlation of the time series as measured by the correlogram.     

More on progressively Type‐II censored order statistics for multivariate observations

In this paper, we consider some results on distribution theory of multivariate progressively Type‐II censored order statistics. We also establish some characterizations of Freund's bivariate exponential distribution based on the lack of memory property.     

Automatic Block-Length Selection for the Dependent Bootstrap

Abstract

We review the different block bootstrap methods for time series, and present them in a unified framework. We then revisit a recent result of Lahiri [Lahiri, S. N. (1999b). Theoretical comparisons of block bootstrap methods, Ann. Statist. 27:386–404] comparing the different methods and give a corrected bound on their asymptotic relative efficiency; we also introduce a new notion of finite-sample “attainable” relative efficiency. Finally, based on the notion of spectral estimation via the flat-top lag-windows of Politis and Romano [Politis, D. N., Romano, J. P. (1995). Bias-corrected nonparametric spectral estimation. J. Time Series Anal. 16:67–103], we propose practically useful estimators of the optimal block size for the aforementioned block bootstrap methods. Our estimators are characterized by the fastest possible rate of convergence which is adaptive on the strength of the correlation of the time series as measured by the correlogram.     

A note on circular neighbor balanced designs

ABSTRACT

This paper describes some methods of constructing circular neighbor balanced and circular partially neighbor balanced block designs for estimation of direct and neighbor effects of the treatments. A class of circular neighbor balanced block designs with unequal block sizes is also proposed.     

Model Order Estimation of a Multivariable Stochastic Process

ABSTRACT

This article presents a procedure allowing us to estimate the minimal order of a state-space representation, for a multivariable stochastic process, from a sequence of observations. The method proposes a statistical rule for testing the rank of a block Hankel matrix of data, since this rank is related to the order of the process. A new information criterion is then developed and used to decide upon the order of the model. In this article we generalize the Aoki C-test. Using two representative data sets as the basis for a Monte Carlo experiment and real data based on Danish economy, we estimate the order of multivariable stochastic processes.     

Partially A-optimal blocked multi-factor designs

In this paper, we propose a partially A-optimal criterion for block designs where multiple factors are arranged. The number of levels of each factor is assumed to be arbitrary and unequal block sizes are allowed. A sufficient condition is derived for a design to be partially A-optimal among all feasible designs. Then the properties of the selected design and its relation with orthogonal arrays are studied. Methods of constructing designs satisfying the sufficient condition are also given.