Generating autocorrelated pseudo-random numbers with specific distributions

An easily implemented and computationally efficient procedure is presented for the generation of autocorrelated pseudo-random numbers with specific probability distributions. A plot illustrates the relationship among the autocorrelations of the uniform, Rayleigh, and exponential distributions corresponding to a given autocorrelation in the normal generating distribution.     

On the generation of subsets of order statistics

A modification of Schucany's (1972) method for generating order statistics is given which allows for efficient generation of certain subsets of order statistics.     

Prediction of Variables Via Their Order Statistics in Bivariate Elliptical Distributions with Application in the Financial Markets

Assuming that (X₁, X₂) has a bivariate elliptical distribution, we obtain an exact expression for the joint probability density function (pdf) as well as the corresponding conditional pdfs of X₁ and X₍₂₎ ? max?{X₁, X₂}. The problem is motivated by an application in financial markets. Exchangeable random variables are discussed in more detail. Two special cases of the elliptical distributions that is the normal and the student’s t models are investigated. For illustrative purposes, a real data set on the total personal income in California and New York is analyzed using the results obtained. Finally, some concluding remarks and further works are discussed.     

A multivariate two-factor skew model

It is well known that many data, such as the financial or demographic data, exhibit asymmetric distributions. In recent years, researchers have concentrated their efforts to model this asymmetry. Skew normal model is one of such models that are skew and yet possess many properties of the normal model. In this paper, a new multivariate skew model is proposed, along with its statistical properties. It includes the multivariate normal distribution and multivariate skew normal distribution as special cases. The quadratic form of this random vector follows a χ² distribution. The roles of the parameters in the model are investigated using contour plots of bivariate densities.     

Moments of a ratio of two quadratic forms

In this paper, we give the exact moments of a ratio of qua- dratic forms in normal variables, where the quadratic forms are not assumed to be independent. This problem was tackled by other authors who gave approximations and partial results. Here we will give the exact moments for the general case.     

ATM接入网络中非对称性周期传输过程分析

利用嵌入Markov链和概率母函数，对ATM接入网络中离散时间情况下的非对称周期查询门限服务模型进行了数学解析。并进行了计算机模拟，模拟结果与理论分析吻合。     

Bounds for the error in an approximation to the distribution of continuous random vectors with bounded supports

An approximation for the distributions of m-dimensional random variables with absolutely continuous cumulative distribution functions and bounded supports is presented. In addition, two easily computed bounds for the error in using the approximation rather than the actual distribution are provided for any measurable region.     

Some New Discrete Probability Distributions Derived from Power Series Distributions

Power series distributions (PSD) are well documented in the literature. Some of the well-known theoretical models in statistics, like Poisson, negative binomial, and geometric, belong to this family. Many real-life phenomena are represented by these models. Based on these models, some new probability distributions are obtained in this paper. By means of examples it is demonstrated that the derived distributions fit the situations better than the existing models.     

微型风力发电机组电气电控系统设计要求的分析

文章从使用要求出发,分析了微型风力发电机组电气电控系统的设计要求。     

Linear approximate ML estimation in scaled Type I generalized logistic distribution based on Type-II censored samples

The scaled (two-parameter) Type I generalized logistic distribution (GLD) is considered with the known shape parameter. The ML method does not yield an explicit estimator for the scale parameter even in complete samples. In this article, we therefore construct a new linear estimator for scale parameter, based on complete and doubly Type-II censored samples, by making linear approximations to the intractable terms of the likelihood equation using least-squares (LS) method, a new approach of linearization. We call this as linear approximate maximum likelihood estimator (LAMLE). We also construct LAMLE based on Taylor series method of linear approximation and found that this estimator is slightly biased than that based on the LS method. A Monte Carlo simulation is used to investigate the performance of LAMLE and found that it is almost as efficient as MLE, though biased than MLE. We also compare unbiased LAMLE with BLUE based on the exact variances of the estimators and interestingly this new unbiased LAMLE is found just as efficient as the BLUE in both complete and Type-II censored samples. Since MLE is known as asymptotically unbiased, in large samples we compare unbiased LAMLE with MLE and found that this estimator is almost as efficient as MLE. We have also discussed interval estimation of the scale parameter from complete and Type-II censored samples. Finally, we present some numerical examples to illustrate the construction of the new estimators developed here.