A test for normality

Summary An analogue of the C ramer - von M ism W ²-statistic is given for testing the composite hypothesis of normality with unspecified parameters. Some Monte Carlo percentiles of this statistic are provided. A power comparison with the test developed in [4] shows that the present test is better against certain alternatives.     

A maximin test for means

Summary Let X be a normal vector with mean μ and known covariance matrix. This note is concerned with the problem of showing that the test based on X^-1X is maximin most powerful for μ= 0 versus μ belongs to a given ellipsoid and uniformly most powerful for μ = 0 versus μ belongs to a family of ellipsoids.     

离合器试验台设计

文章阐述了惯性式离合器试验台的用途、试验方法以及达到的主要性能指标,分析了原有试验台存在的问题,提出了新的改进设计方案,并对主要改进设计部分进行了分析和论述。     

Controlling for ability using test scores

This paper proposes a semiparametric method to control for ability using standardized test scores, or other item response assessments, in a regression model. The proposed method is based on a model in which the parameter of interest is invariant to monotonic transformations of ability. I show that the estimator is consistent as both the number of observations and the number of items on the test grow to infinity. I also derive conditions under which this estimator is root‐n consistent and asymptotically normal. The proposed method is easy to implement, does not impose a parametric item response model, and does not require item‐level data. I demonstrate the finite‐sample performance in a Monte Carlo study and implement the procedure for a wage regression using data from the NLSY1979.     

A moment-based test for extreme-value dependence

This paper proposes a new rank-based test of extreme-value dependence. The procedure is based on the first three moments of the bivariate probability integral transform of the underlying copula. It is seen that the test statistic is asymptotically normal and its finite- and large-sample variance are calculated explicitly. Consistent plug-in estimators for the variance are proposed, and a fast algorithm for their computation is given. Although it is shown via counterexamples that no test based on the probability integral transform can be consistent, the proposed procedure achieves good power against common alternatives, both in finite samples and asymptotically.     

An outlier test for linear processes

In this paper we introduce an outlier test for linear processes. It is assumed that an upper bound for the number of outliers is known which is not too big in relation to the sample size. The test statistic bases on the comparison of the observations with certain predictors. We discuss the asymptotical behaviour of the test statistic under the null hypothesis ‘no outlier’ and derive the asymptotic distribution for the case that the distribution of the squared white noise process belongs to a certain subset of the domain of attraction of the Gumbel distribution. Especially the most important case in applications, the Gaussian white noise is included.     

A non-parametric test for industrial specialization

We introduce a non-parametric microdata based test for industrial specialization and apply it to a single urban area. Our test employs establishment densities for specific industries, a population counterfactual, and a new correction for multiple hypothesis testing to determine the statistical significance of specialization across both places and industries. Results highlight patterns of specialization that are extremely varied, with downtown places specializing in a number of service sector industries, while suburban places specialize in both manufacturing and service industries. Business service industries are subject to more specialization than non-business service industries while the manufacturing sector contains the lowest representation of industries with specialized places. Finally, we compare results for specialization with localization and show that both measures contribute to our understanding of industry and place specific agglomerative forces.     

A nonparametric test for changing trends

Many tests of parameter change in dynamic models exhibit nonmonotonic power. An important source of the nonmonotonic power comes from the bias in estimating parameters when there is a change in the deterministic component. To avoid this bias, we propose a nonparametric test for changing trends based on nonparametrically detrended data. The tests are similar in spirit to nonparametric conditional moment tests such as Fan and Li (J. Nonparametr. Stat. 10 (1999a) 245; 11 (1999b) 251) and Zheng (J. Econometrics 75 (1996) 263). The resulting statistics have a standard normal distribution. A Monte Carlo experiment suggests that the tests have good power against changes in the deterministic component.     

A low-dimension portmanteau test for non-linearity

A new test for non-linearity in the conditional mean is proposed using functions of the principal components of regressors. The test extends the non-linearity tests based on Kolmogorov–Gabor polynomials (,  and ), but circumvents problems of high dimensionality, is equivariant to collinearity, and includes exponential functions, so is a portmanteau test with power against a wide range of possible alternatives. A Monte Carlo analysis compares the performance of the test to the optimal infeasible test and to alternative tests. The relative performance of the test is encouraging: the test has the appropriate size and has high power in many situations.     

A test for randomness in behaviour

In biological analysis of behaviour, transition matrices occur of which the diagonal entries are essentially zero. For such transition matrices, a model of randomness is constructed, with a test for the hypothesis that this model holds.     

EPS硬件在环测试系统设计

针对传统电控单元开发方法对ECU测试的不足,研究电动助力转向系统电控单元的硬件在环仿真测试系统,详细介绍了硬件在环测试系统的构成及各个子系统的建立过程,并基于Matlab/Simulink建立了硬件在环仿真测试系统各个部分的仿真模型.     

A two-stage test for one-way analysis of variance

A two-stage analogue of the Ftest for one-way analysis of variance is proposed. Critical values are given for selected cases and the method of obtaining critical values is described. Comparisons of the one-stage and two-stage tests are made in terms of the expected sample size required to achieve a given power.     

A variety of criteria for setting test limits

In the inspection of manufactured parts, measurements of the characteristic of interest are subject to, typically small, measurement errors. Hence, there is need for a test limit which is typically more strict than the specification limit. In this paper we will discuss various criteria on which such test limits can be based.     

A test for equality of two exponential distributions

Abstract Let X ₁., X _n1 and Y ₁., Y _n1, be two independent random samples from exponential populations. The statistical problem is to test whether or not two exponential populations are the same, based on the order statistics X _[1],. X _[r1] and Y [₁],. Y _[rs] where 1 r₁ n ₁ and 1 r₂ n ₂. A new test is given and an asymptotic optimum property of the test is proved.     

Change point test for tail index for dependent data

To test for the constancy of tail index, Quintos et al. (Rev Econ Stud 68:633–663, 2001) proposed three types of change point tests for independent and ARCH type sequences. In this paper, we demonstrate that their tests can be successfully extended to a large class of dependent stationary sequences. Further, we designate a time-reverse version of those tests since the original tests produce very low powers in case the tail of distribution gets thinner. A simulation study is implemented for illustration.     

A point optimal test for autoregressive disturbances

This paper is concerned with testing for first-order autoregressive disturbances in the linear regression model and recommends an alternative test to the Durbin-Watson test. The new test is most powerful invariant in a given neighbourhood of the alternative hypothesis parameter space. An empirical power comparison indicates that the test is generally more powerful than the Durbin-Watson test. The comparison also suggests that for many economic applications, the difference in power will be small, although circumstances do exist in which the power advantage of the new test is very real. Selected bounds for the test's significance points are tabulated.     

Distrubition-free test for homogeneity against stochastic ordering

Two classes of distribution-free tests for homogeneity of several populations agaist stochastic ordering are proposed. One class of tests is shown to perform better for homogeneity of scale against ordered alternative, where as other class of tests is shown to be better for homogeneity of locations against their ordering.     

The Bierens test for certain nonstationary models

We adapt the Bierens (1990) test to the I-regular models of Park and Phillips (2001). Bierens (1990) defines the test hypothesis in terms of a conditional moment condition. Under the null hypothesis, the moment condition holds with probability one. The probability measure used is that induced by the variables in the model, that are assumed to be strictly stationary. Our framework is nonstationary and this approach is not always applicable. We show that the Lebesgue measure can be used instead in a meaningful way. The resultant test is consistent against all I-regular alternatives.     

A new poolability test for cointegrated panels

This paper proposes a new test of the null hypothesis that the parameters in a cointegrated panel data regression are equal across the cross‐section. The asymptotic distribution of the new test statistic is derived and simulation results are provided to suggest that it performs very well in small samples. An empirical application to the monetary exchange rate model is also provided. Copyright © 2009 John Wiley & Sons, Ltd.     

A goodness-of-fit test for GARCH innovation density

We prove asymptotic normality of a suitably standardized integrated square difference between a kernel type error density estimator based on residuals and the expected value of the error density estimator based on innovations in GARCH models. This result is similar to that of Bickel–Rosenblatt under i.i.d. set up. Consequently the goodness-of-fit test for the innovation density of GARCH processes based on this statistic is asymptotically distribution free, unlike the tests based on the residual empirical process. A simulation study comparing the finite sample behavior of this test with Kolmogorov–Smirnov test and the test based on integrated square difference between the kernel density estimate and null density shows some superiority of the proposed test.