Unaliasing of aliased line component frequencies

This paper is concerned with undoing aliasing effects, which arise from discretely sampling a continuous‐time stochastic process. Such effects are manifested in the frequency‐domain relationships between the sampled and original processes. The authors describe a general technique to undo aliasing effects, given two processes, one being a time‐delayed version of the other. The technique is based on the observations that certain phase information between the two processes is unaffected by sampling, is completely determined by the (known) time delay, and contains sufficient information to undo aliasing effects. The authors illustrate their technique with a simulation example. The theoretical model is motivated by the helioseismological problem of determining modes of solar pressure waves. The authors apply their technique to solar radio data, and conclude that certain low‐frequency modes known in the helioseismology literature are likely the result of aliasing effects. The Canadian Journal of Statistics 38: 116–135; 2010 © 2010 Statistical Society of Canada     

Partitioning k multivariate normal populations according to equivalence with respect to a standard vector

We propose optimal procedures to achieve the goal of partitioning k multivariate normal populations into two disjoint subsets with respect to a given standard vector. Definition of good or bad multivariate normal populations is given according to their Mahalanobis distances to a known standard vector as being small or large. Partitioning k multivariate normal populations is reduced to partitioning k non-central Chi-square or non-central F distributions with respect to the corresponding non-centrality parameters depending on whether the covariance matrices are known or unknown. The minimum required sample size for each population is determined to ensure that the probability of correct decision attains a certain level. An example is given to illustrate our procedures.     

Some properties of tests for parameters that can be arbitrarily close to being unidentified

Confidence intervals for parameters that can be arbitrarily close to being unidentified are unbounded with positive probability [e.g. Dufour, J.-M., 1997. Some impossibility theorems in econometrics with applications to instrumental variables and dynamic models. Econometrica 65, 1365–1388; Pfanzagl, J. 1998. The nonexistence of confidence sets for discontinuous functionals. Journal of Statistical Planning and Inference 75, 9–20], and the asymptotic risks of their estimators are unbounded [Pötscher, B.M., 2002. Lower risk bounds and properties of confidence sets for ill-posed estimation problems with applications to spectral density and persistence estimation, unit roots, and estimation of long memory parameters. Econometrica 70, 1035–1065]. We extend these “impossibility results” and show that all tests of size α concerning parameters that can be arbitrarily close to being unidentified have power that can be as small as α for any sample size even if the null and the alternative hypotheses are not adjacent. The results are proved for a very general framework that contains commonly used models.     

Normal approximation to the hypergeometric distribution in nonstandard cases and a sub-Gaussian Berry–Esseen theorem

In this paper, we consider simple random sampling without replacement from a dichotomous finite population. We investigate accuracy of the Normal approximation to the Hypergeometric probabilities for a wide range of parameter values, including the nonstandard cases where the sampling fraction tends to one and where the proportion of the objects of interest in the population tends to the boundary values, zero and one. We establish a non-uniform Berry–Esseen theorem for the Hypergeometric distribution which shows that in the nonstandard cases, the rate of Normal approximation to the Hypergeometric distribution can be considerably slower than the rate of Normal approximation to the Binomial distribution. We also report results from a moderately large numerical study and provide some guidelines for using the Normal approximation to the Hypergeometric distribution in finite samples.     

Rényi statistics for testing hypotheses in mixed linear regression models

Rényi divergences are used to propose some statistics for testing general hypotheses in mixed linear regression models. The asymptotic distribution of these tests statistics, of the Kullback–Leibler and of the likelihood ratio statistics are provided, assuming that the sample size and the number of levels of the random factors tend to infinity. A simulation study is carried out to analyze and compare the behavior of the proposed tests when the sample size and number of levels are small.     

On the detection of changes in autoregressive time series I. Asymptotics

Various test statistics are discussed which can be used for detecting changes in the parameters of an autoregressive time series. In this first part of our study, the limiting behavior of the test statistics is derived under the null hypothesis of no change as well as under alternatives. In a forthcoming second part of our investigation, these asymptotic results will be compared to some corresponding bootstrap procedures, and a small simulation study will be conducted.     

On robust forecasting in dynamic vector time series models

In this article, robust estimation and prediction in multivariate autoregressive models with exogenous variables (VARX) are considered. The conditional least squares (CLS) estimators are known to be non-robust when outliers occur. To obtain robust estimators, the method introduced in Duchesne [2005. Robust and powerful serial correlation tests with new robust estimates in ARX models. J. Time Ser. Anal. 26, 49–81] and Bou Hamad and Duchesne [2005. On robust diagnostics at individual lags using RA-ARX estimators. In: Duchesne, P., Rémillard, B. (Eds.), Statistical Modeling and Analysis for Complex Data Problems. Springer, New York] is generalized for VARX models. The asymptotic distribution of the new estimators is studied and from this is obtained in particular the asymptotic covariance matrix of the robust estimators. Classical conditional prediction intervals normally rely on estimators such as the usual non-robust CLS estimators. In the presence of outliers, such as additive outliers, these classical predictions can be severely biased. More generally, the occurrence of outliers may invalidate the usual conditional prediction intervals. Consequently, the new robust methodology is used to develop robust conditional prediction intervals which take into account parameter estimation uncertainty. In a simulation study, we investigate the finite sample properties of the robust prediction intervals under several scenarios for the occurrence of the outliers, and the new intervals are compared to non-robust intervals based on classical CLS estimators.     

《101/2章世界史》中的反讽艺术

《10 1/2章世界史》是英国当代作家朱利安.巴恩斯的代表作之一。作者以《圣经》中的诺亚方舟为基本意象,敷衍出10 1/2章故事,同时以反讽的姿态重新审视神话传说和历史事件,在有限的篇幅内展现出了一幅独特的人类历史画卷。     

Robust estimating equation based on statistical depth

In this paper the estimating equation is constructed via statistical depth. The obtained estimating equation and parameter estimation have desirable robustness, which attain very high breakdown values close to 1/2. At the same time, the obtained parameter estimation still has ordinary asymptotic behaviours such as asymptotic normality. In particular, the robust quasi likelihood and depth-weighted LSE respectively for nonlinear and linear regression model are introduced. A suggestion for choosing weight function and a method of constructing depth-weighed quasi likelihood equation are given. This paper is supported by NNSF projects (10371059 and 10171051) of China.     

UNEMPLOYMENT INSURANCE AND CULTURAL TRANSMISSION: THEORY AND APPLICATION TO EUROPEAN UNEMPLOYMENT

This paper emphasizes the two‐way causality between the provision of unemployment insurance and the cultural transmission of civicness. The returns to being uncivic are increasing in the generosity of unemployment insurance; but this generosity is decreasing in the number of uncivic individuals. In this context, I determine the evolution of preferences across generations and show that cultural heterogeneity is sustained over the long‐run. The dynamics of cultural transmission can generate a long lag between the introduction of unemployment insurance and an increase in people's willingness to live off government‐provided benefits. Hence, it offers an explanation to the ‘European unemployment puzzle’ due to the coexistence of generous unemployment insurance and low unemployment in the 1950s and 1960s.