Moments of nonparametric probability density functions of entropy estimators applied to testing the inverse Gaussian distribution

The inverse Gaussian (IG) distribution is widely used to model data and then it is important to develop efficient goodness of fit tests for this distribution. In this article, we introduce some new test statistics for examining the IG goodness of fit based on correcting moments of nonparametric probability density functions of entropy estimators. These tests are consistent against all alternatives. Critical points and power of the tests are explored by simulation. We show that the proposed tests are more powerful than competitor tests. Finally, the proposed tests are illustrated by real data examples.     

Asymptotic normality of estimators for parameters of a multivariate skew-normal distribution

In this paper, asymptotic normality is established for the parameters of the multivariate skew-normal distribution under two parametrizations. Also, an analytic expression and an asymptotic normal law are derived for the skewness vector of the skew-normal distribution. The estimates are derived using the method of moments. Convergence to the asymptotic distributions is examined both computationally and in a simulation experiment.     

β-Skeleton depth functions and medians

We define the β-skeleton depth based on the probability that a point is contained within the β-skeleton influence region of two i.i.d. random vectors. The proposed family of depth functions satisfies the four desirable properties of statistical depth function. We also define and examine the sample β-skeleton depth functions and show that they share well-behaved asymptotic properties, including uniform consistency and asymptotic normality. Finally, we explore the β-skeleton multidimensional medians as location estimators of the center of multivariate distributions, discuss its asymptotic properties, and study its breakdown point. A Monte Carlo study compares the β-skeleton medians with the random Tukey median and the sample mean.     

A consistent estimator of the smoothing operator in the functional Hodrick–Prescott filter

In this article, we consider a version of the functional Hodrick–Prescott filter for functional time series. We show that the associated optimal smoothing operator preserves the “noise-to-signal ratio” structure. Moreover, as the main result, we propose a consistent estimator of this optimal smoothing operator.     

Parameter estimation in multivariate logit models with many binary choices

Multivariate Logit models are convenient to describe multivariate correlated binary choices as they provide closed-form likelihood functions. However, the computation time required for calculating choice probabilities increases exponentially with the number of choices, which makes maximum likelihood-based estimation infeasible when many choices are considered. To solve this, we propose three novel estimation methods: (i) stratified importance sampling, (ii) composite conditional likelihood (CCL), and (iii) generalized method of moments, which yield consistent estimates and still have similar small-sample bias to maximum likelihood. Our simulation study shows that computation times for CCL are much smaller and that its efficiency loss is small.     

Extropy estimators with applications in testing uniformity

Two estimators for estimating the extropy of an absolutely continuous random variable with known support were introduced by using spacing. It is shown that the proposed estimators are consistent and their mean square errors are shift invariant. Their behaviours were also studied by means of real data and Monte Carlo simulation. The winner estimator of extropy in the Monte Carlo experiment was used to develop goodness-of-fit test for standard uniform distribution. It is shown that the extropy-based test that we proposed performs well by comparing its powers with that of other tests for uniformity.     

用矩阵讨论多元函数的极值问题

利用矩阵给出了多元函数在稳定点取极值的充分条件,提出了解决两类极值问题的代数方法.     

GARCH-M模型与我国沪深股市的波动

运用多元GARCH-M模型对我国沪、深股市的期望收益率与 风险以及两市波动之间的相互影响关系进行了实证性研究，发现我国股市风险和期望收益之 间无显著关联，但两市波动之间存在着相互影响的关系。同时，沪、深股市波动具有群集性 和持续性。     

Multivariate signed rank statistics for shift alternatives

Let X ₁,X ₂,…,X _N be successive independent random P-vectors drawn from some continuous diagonally symmetric distribution. The problem of detecting a shift in level of the sequence at an unknown time point M, ≦M ≦ N-1, is studied. Test statistics based on multivariate analogues of the rank statistics derived by BHATTACHARYYA and JOHNSON (1888) are proposed, and their asymptotic properties are investigated.