关于现行外商直接投资统计管理的思考

准确统计外商直接投资是正确估计经济发展速度的重要条件之一。招商引资指标考核、免征进口关税的优惠条件 ,以及企业错漏申报、未及时验资等是导致现行外商直接投资统计方法在不同口径的统计数据之间产生显著偏差的主要原因。规范外商直接投资统计方法、加强投资物品进口审核和外汇资金流入监管力度、完善国际收支统计申报和外资外汇登记工作是改进现行外商直接投资的统计与管理的可行方法。     

正态分布基于顺序统计量的一个结果

关于正态分布总体给出了由两顺序统计量构成的一个函数，并讨论了其概率分布。这个结果可用于不完全的样本数据以及样本中可能存在异常值时，正态总体位置参数的区间估计。     

双参数指数分布异常数据的检验

针对双参数指数分布的异常大数据,给出了一种新的检验方法。寻找到总体参数的具有较好稳健性的估计量,并在此基础上构造出检验统计量,求出了该检验统计量精确的概率密度函数和大样本情形下的近似分布,得到了检验临界值简洁的近似表达式。     

井口声发射井筒液气浸检测—时延估计方法

基于高阶统计,提出了井口声发射井筒液气浸检测中的接收和发射声信号之间时延估计的非参数化和参数化方法。通过分析声信号在井筒液中的传播过程,井口声发射井筒液气浸检测中的接收噪声,可近似模型化为空间相关的高斯色噪声。由于四阶累积量对任意高斯噪声的盲目性,因此,较常规互相关估计方法,这些方法可以进一步提高检测概率。计算机模拟结果证实了它们的有效性。     

Uniform asymptotic linearity in a regression parameter of a process based on a rank statistic

For X₁, …, X_N a random sample from a distribution F, let the process S^δ_N(t) be defined as where K²_N = σ^N_i=1(c_i ? c?)² and R x_i, + Δd, is the rank of X_i + Δd_i, among X₁ + Δd₁, …, X_N + Δd_N. The purpose of this note is to prove that, under certain regularity conditions on F and on the constants c_i and d_i, S^Δ_N (t) is asymptotically approximately a linear function of Δ, uniformly in t and in Δ, |Δ| ≤ C. The special case of two samples is considered.     

A new diagnostic tool for VARMA(p,q) models

A new diagnostic method for VARMA(p,q) time series models is introduced. The procedure is based on a statistic that generalizes to a multivariate setting the properties of the usual univariate ARMA(p,q) residual correlations. A multiple version of the cumulative periodogram statistic is also suggested. Simulation studies and one real data application are presented.     

On approximating the distribution of indefinite quadratic forms

This paper provides a simple methodology for approximating the distribution of indefinite quadratic forms in normal random variables. It is shown that the density function of a positive definite quadratic form can be approximated in terms of the product of a gamma density function and a polynomial. An extension which makes use of a generalized gamma density function is also considered. Such representations are based on the moments of a quadratic form, which can be determined from its cumulants by means of a recursive formula. After expressing an indefinite quadratic form as the difference of two positive definite quadratic forms, one can obtain an approximation to its density function by means of the transformation of variable technique. An explicit representation of the resulting density approximant is given in terms of a degenerate hypergeometric function. An easily implementable algorithm is provided. The proposed approximants produce very accurate percentiles over the entire range of the distribution. Several numerical examples illustrate the results. In particular, the methodology is applied to the Durbin–Watson statistic which is expressible as the ratio of two quadratic forms in normal random variables. Quadratic forms being ubiquitous in statistics, the approximating technique introduced herewith has numerous potential applications. Some relevant computational considerations are also discussed.     

On detecting outliers in the Pareto distribution

In this paper, we introduce two new statistics for detecting outliers in the Pareto distribution. These new statistics are the extension of the statistics for detecting outliers in exponential and gamma distributions. In fact, we compare the power of our test statistics with the other statistics and select the best test statistic for detecting outliers in the Pareto distribution. Finally, numerical examples of different insurance claims are used to see the performance of the test.     

A density-based empirical likelihood ratio goodness-of-fit test for the Rayleigh distribution and power comparison

The Rayleigh distribution has been used to model right skewed data. Rayleigh [On the resultant of a large number of vibrations of the some pitch and of arbitrary phase. Philos Mag. 1880;10:73–78] derived it from the amplitude of sound resulting from many important sources. In this paper, a new goodness-of-fit test for the Rayleigh distribution is proposed. This test is based on the empirical likelihood ratio methodology proposed by Vexler and Gurevich [Empirical likelihood ratios applied to goodness-of-fit tests based on sample entropy. Comput Stat Data Anal. 2010;54:531–545]. Consistency of the proposed test is derived. It is shown that the distribution of the proposed test does not depend on scale parameter. Critical values of the test statistic are computed, through a simulation study. A Monte Carlo study for the power of the proposed test is carried out under various alternatives. The performance of the test is compared with some well-known competing tests. Finally, an illustrative example is presented and analysed.