Locally minimax test of independence in elliptically symmetrical distributions with additional observations

Summary LetX=(X _ij )=(X ₁, ...,X _n )’,X’ _i =(X _i1, ...,X _ip )’,i=1,2, ...,n be a matrix having a multivariate elliptical distribution depending on a convex functionq with parameters, 0,σ. Let ϱ²=ϱ ₂ ^-2 be the squared multiple correlation coefficient between the first and the remainingp ₂+p ₃=p−1 components of eachX _i . We have considered here the problem of testingH ₀:ϱ²=0 against the alternativesH ₁:ϱ ₁ ^-2 =0, ϱ ₂ ^-2 >0 on the basis ofX andn ₁ additional observationsY ₁ (n ₁×1) on the first component,n ₂ observationsY ₂(n ₂×p ₂) on the followingp ₂ components andn ₃ additional observationsY ₃(n ₃×p ₃) on the lastp ₃ components and we have derived here the locally minimax test ofH ₀ againstH ₁ when ϱ ₂ ^-2 →0 for a givenq. This test, in general, depends on the choice ofq of the familyQ of elliptically symmetrical distributions and it is not optimality robust forQ.     

Locally most powerful sequential tests for processes of the exponential class with stationary and independent increments

Sequential tests that are locally most powerful (LMP) for certain one-sided problems in the case of processes of the exponential class with stationary and independent increments are discussed. After having proved the existence of an LMP sequential test in the above setting each LMP test is shown to be a Wald SPRT for a family of paired (conjugate) simple hypotheses.     

Local minimax pointwise estimation of a multivariate density

We consider the problem of the nonparametric minimax estimation of a multivariate density at a given point. A concept of smoothness classes in nonparametric minimax estimation problems is proposed. The smoothness of a function is characterized by the approximability of the function at a point by an integral of the product of this function with an approximate identity. We propose a singular integral estimator, an integral of this approximate identity with respect to the empirical distribution function. Under some assumptions on the approximate identity, the bias of the estimator is shown to be of smaller order asymptotically than the variance, and the estimator itself is shown to be asymptotically locally minimax with respect to the quadratic risk in a proper topology.     

Coalitional stability in the location problem with single-dipped preferences: An application of the minimax theorem

This study considers a situation in which agents choose the location of a public facility from a street according to a given mechanism. Agents have single-dipped preferences over a set of feasible locations. We analyze coalitional behavior for any given mechanism for this situation. We identify a necessary and sufficient condition for a mechanism to possess a strong Nash equilibrium by applying the minimax theorem of von Neumann and Morgenstern (1944). We introduce a class of core solutions and show that these solutions are characterized by strong Nash implementability. As a byproduct of these results, we propose a simple mechanism that implements any core solution in strong Nash equilibria.     

Score tests for zero covariances in recursive linear models for grouped or censored data

The score test statistic for testing whether an error covariance is zero is derived for a normal linear recursive model for fully observed, censored or grouped data. The test, which is obtained by regarding non-zero error covariances as arising from correlated random parameter variation, is shown to be closely related to the Information Matrix test. It turns out that the statistic, which is asymptotically N[0,1] under the null, examines the sample covariance of appropriately defined residuals.     

Stability and integrity tests in data envelopment analysis

Studies that apply data envelopment analysis often neglect testing the stability of the efficient frontier to data perturbations, and, to a lesser extent, the ability of efficiency scores to correctly discriminate between units on performance (integrity). Our primary motivation is to demonstrate methods that can help reduce the number of managerial decisions based on results that may be unreliable. To this end, we illustrate multiple tests of stability and integrity in an environment of fully units-invariant efficiency measurement. This application of tests of stability and integrity using a slacks-based measure of efficiency is the first in a peer-reviewed journal.     

Linear rank tests for comparing treatments with a control when data are subject to unequal patterns of censorship

A class of asymptotically distribution-free tests is considered for comparing several treatments with a control when the, data are subject to unequal right-censorship. A particular member of this class is proposed for use in practice and an illustrative numerical example is given. A general result for the Pitman efficacy of a test based on an asymptotically normal test statistic is proved for the multiparameter case and using this result the efficacy of the proposed class of tests is obtained under sequences of translation and proportional hazards alternatives. Simulation studies are conducted to compare the performance of the proposed test, in terms of power, with some other tests.     

Some simple structure significance tests for exploratory component analysis with market survey data

Several uncertainties continue to hinder researchers using exploratory factor analysis. Among other decisions, the choice of the number of factors to retain and the interpretability of the rotated solution remain problematical. In this paper, we suggest a simple structure criterion as a general framework for choosing the number of factors and for interpreting the rotated factor structure matrix. The proposed methodology is demonstrated with demographic data from a consumer panel. The results show the importance of increasing the information yield from exploratory factor analysis.     

Exact linear rank tests for two‐sample equivalence problems with continuous data

The present paper introduces a methodology for the semiparametric or non‐parametric two‐sample equivalence problem when the effects are specified by statistical functionals. The mean relative risk functional of two populations is given by the average of the time‐dependent risk. This functional is a meaningful non‐parametric quantity, which is invariant under strictly monotone transformations of the data. In the case of proportional hazard models, the functional determines just the proportional hazard risk factor. It is shown that an equivalence test of the type of the two‐sample Savage rank test is appropriate for this functional. Under proportional hazards, this test can be carried out as an exact level α test. It also works quite well under other semiparametric models. Similar results are presented for a Wilcoxon rank‐sum test for equivalence based on the Mann–Whitney functional given by the relative treatment effect.     

Analysis of a change-point regression problem in quality control by partial sums processes and Kolmogorov type tests

In practice, it is an important problem (especially in quality control) to secure that a known regression function occurs during a certain period in time. In the present paper, we consider the change-point problem that under the null hypothesis this known regression function occurs. As alternative, we consider a certain non-parametric class of functions that is of particular interest in quality control. We analyze this test problem by using partial sums of the data. Asymptotically, we get Brownian motion and Brownian motion with trend (≠0) under the hypothesis and under the alternative, respectively. We prove that tests based on partial sums have a larger power when the partial sums are taken from the time reversed data. This can be quantitatively determined in an asymptotic way by some new results on Kolmogorov type tests for Brownian motion with trend. We illustrate our results by a certain model that is interesting in quality control and by an example with real data.Supported in part by the Deutsche Forschungsgemeinschaft Grant Bi655.Supported in part by the Deutsche Forschungsgemeinschaft Grant Bi655 and by the Swiss National Science Foundation Grant 20-55586.98.     

On the performance of tests by Wu and by Hausman for detecting the ordinary least squares bias problem

We first consider the performance of the Wu (1973) - Hausman (1978) (W-H) specification error test as a test for the existence of ordinary least squares (OLS) bias. We discuss power properties of the test under alternative null hypotheses, one of which has not previously been considered. We next consider how the W-H test performs as an indicator of the extent (rather than the existence) of an OLS bias problem, since this usage of the test seems common in applied studies. Finally Monte Carlo methods are used to evaluate Wu's two-step estimation procedure involving the W-H test as a pretest.     

Locally Most Powerful and Other Rank Tests for Independence – with a Contaminated Weighted Alternative

Several authors in the literature have attempted the quantification of the concept of stochastic dependence for bivariate distribution. Two weighted rank tests for testing independence against a weighted contamination alternative is proposed and their distributional properties are studied. We also derived a locally most powerful rank test for the alternative setting. The rank tests proposed are shown to be asymptotic locally most powerful for specific distributions.     

Use of a median test for a generalized Behrens-Fisher problem

Summary A non-parametric test is proposed for testing differences of location in two independent samples without assuming equal scale parameters of the respective populations. The test is based on simultaneous application of two modified median tests, each using its sample median of the single samples.     

Asymptotically distribution-free tests for the volatility function of a diffusion

This paper develops two tests for parametric volatility function of a diffusion model based on Khmaladze (1981)’s martingale transformation. The tests impose no restrictions on the functional form of the drift function and are shown to be asymptotically distribution-free. The tests are consistent against a large class of fixed alternatives and have nontrivial power against a class of root-n$n$ local alternatives. The paper also extends the tests of volatility to testing for joint specifications of drift and volatility. Monte Carlo simulations show that the tests perform well in finite samples. The proposed tests are then applied to testing models of short-term interest, using data of Treasury bill rate and Eurodollar deposit rate. The empirical results show that the commonly used CKLS volatility function of Chan et al. (1992) fits volatility function poorly and none of the parametric interest rate models considered in the paper fit data well.     

The restricted regularity of admissible minimax criteria for many well known parametric statistical problems

Summary The stability of test selection criteria is a question that was raised byLeCam in 1964 [seeLeCam, 1964], but which seems to have received very little subsequent attention. Roughly, the problem posed byLeCam was to decide whether a given criterion is regular at a given statistical problem, i.e. given that the criterion prescribes the test ₀ for the statistical problem, (₀,D ₀,R ₀), whether it prescribes a best which is nearly the same as ₀ for any statistical problem, (, D,R), near to (₀, D₀,R ₀).A more precise formulation ofLeCam's question is one of the objectives of this paper. This involves defining a suitable topology on the domain of problems where the criterion in question is to be applied. Elementary minimax results of a general nature are proved, and counter examples are given to show that the assumptions used are not completely superfluous. The generality of these results seems to lend support to the authors opinion, that the method of formulation is suitable for treating minimax questions. We then consider the standard elementary problems of parametric statistics, (monotone likelihood ratio, general exponential family) and prove that the admissible minimax criterion is regular with respect to certain types of perturbations in these problems. The treatment is, in a sense, restricted and departs fromLeCam in holding the risk function essentially constant while varying the parameter space. That the problem variations considered may be of some practical interest and that the general formulations used are not completely unrealistic is shown at the conclusion of the paper where we apply a rest, icted regularity theorem to obtain regularity results for the binomial case.     

Unbiased estimates for a lognormal regression problem and a nonparametric alternative

Given a normal sample with means \({{\bf x}_{1}^{\prime} {\bf \varphi}, \ldots, {\bf x}_{n}^{\prime} {\bf \varphi}}\) and variance v, minimum variance unbiased estimates are given for the moments of L, where log L is normal with mean \({{\bf x}^{\prime} {\bf \varphi}}\) and variance v. These estimates converge to wrong values if the normality assumption is false. In the latter case estimates based on any M-estimate of \({{\bf \varphi}}\) are available of bias \({O\left(n^{-1}\right)}\) and \({O\left(n^{-2}\right)}\). More generally, these are given for any smooth function of \({\left({\bf \varphi}, F\right)}\), where F is the unknown distribution of the residuals. The regression functions need not be linear.     

A parametric simplex-like algorithm for a fractional programming problem

A few theoretical results are given for the fractional programming problem where the objective function is the product of an affine function and a linear fractional function and where the feasible region is a polytope. Moreover, a simplex-like algorithm is proposed to solve the same problem when the feasible region is bounded. The algorithm is based on the exploration of a set of suitably defined optimal level solutions.

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Riassunto Nel lavoro vengono esposti alcuni risultati teorici per un problema di programmazione frazionaria nel quale la funzione oggetto è data dal prodotto tra una funzione affine e una funzione lineare definita su una regione ammissibile poliedrica. Viene inoltre formulato un algoritmo di tipo simplesso che consente la risoluzione del problema qualora la regione ammissibile sia limitata. Tale algoritmo è basato sulla esplorazione di un insieme opportunamente definito di soluzioni ottime di livello.

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This research was partially supported by MURST.