A note on sum-quota sampling

Kremers'(1986) sum-quota sampling for estimating the mean of a finite population is reviewed. The objective of this note is to point out that the estimate of the variance of Kremers’ estimator could be negative. This negativity also occurs in the sampling schemes discussed in Kremers and Robson (1987). An example is given to substantiate these remarks.     

Use of ranks in probability propoetional to size sampling

Use of ranks in unequal probability sampling is examined for sample selection, stratification as well as determining the strata boundaries. A few sampling schemes are proposed and investigated, For samples of size two, two sampling schemes and their 1PPS versions are discussed, An extension of these schemes to general sample sizes is outlined. Nonnegative unbiased variance estimators are proposed in each case, An empirical comparison is included.     

A New Approach to Importance Sampling in Taylor’s Stochastic Volatility Model

This article presents the general analysis of finite high-dimensional integrals using the Importance Sampling (IS) in aim to the parameter estimation of Taylor’s stochastic volatility (SV) model. After we proceed to make an alternative derivation for Sequential Importance Sampling (SIS) in previous literatures, we propose a new approach to select the optimal parameters of sampler, which is called as Universal Importance Sampling (UIS). UIS minimizes the Monte Carlo variance and numerically performs at least the same accurately as the SIS algorithm, but the computational efficiency get greatly improved. We apply both methods and investigate the SV model on the data, then make comparisons of the results.     

Probability computations for an extension of the geometric distribution

An extension of the stochastic process associated with the geometric distribution is presented. Combinatorial arguments are used to derive probabilities for various events of interest. Probabilities are approximated by evaluating truncated series. Bounds on the errors of approximation are developed. An example is presented and some additional applications are noted.     

A new unrelated question randomized response model

In this paper, we extend the work of Gjestvang and Singh [A new randomized response model, J. R. Statist. Soc. Ser. B (Methodological) 68 (2006), pp. 523–530] to propose a new unrelated question randomized response model that can be used for any sampling scheme. The interesting thing is that the estimator based on one sample is free from the use of known proportion of an unrelated character, unlike Horvitz et al. [The unrelated question randomized response model, Social Statistics Section, Proceedings of the American Statistical Association, 1967, pp. 65–72], Greenberg et al. [The unrelated question randomized response model: Theoretical framework, J. Amer. Statist. Assoc. 64 (1969), pp. 520–539] and Mangat et al. [An improved unrelated question randomized response strategy, Calcutta Statist. Assoc. Bull. 42 (1992), pp. 167–168] models. The relative efficiency of the proposed model with respect to the existing competitors has been studied.     

On the efficiency of monte carlo methods using steady state ranked simulated samples

Samawi (1999) showed that the efficiency of Monte Carlo methods of integrals estimation can be substantially improved by using ranked simulated samples (RSIS) in place of uniform simulated samples (USIS). However, in this paper it is shown that substantial improvement of efficiency can be achieved further by using the steady state ranked simulated sample (SRSIS). It appears that the modified Monte Carlo methods using SRSIS provide unbiased and more efficient estimators for the integrals. Some theoretical properties of SRSIS are given. A simulation study is conducted to compare the performance of the methods using SRSIS with respect to USIS, for some examples.     

Control charts for location based on different sampling schemes

Control charts are the most important statistical process control tool for monitoring variations in a process. A number of articles are available in the literature for the X? control chart based on simple random sampling, ranked set sampling, median-ranked set sampling (MRSS), extreme-ranked set sampling, double-ranked set sampling, double median-ranked set sampling and median double-ranked set sampling. In this study, we highlight some limitations of the existing ranked set charting structures. Besides, we propose different runs rules-based control charting structures under a variety of sampling strategies. We evaluate the performance of the control charting structures using power curves as a performance criterion. We observe that the proposed merger of varying runs rules schemes with different sampling strategies improve significantly the detection ability of location control charting structures. More specifically, the MRSS performs the best under both single- and double-ranked set strategies with varying runs rules schemes. We also include a real-life example to explain the proposal and highlight its significance for practical data sets.     

宽带LFM信号去斜率数字脉压方法性能分析

在宽带LFM信号数字脉压中,去斜率数字脉压方法能有效地降低采样率,但是受到目标回波信号与参考信号的时延差的限制,只能作局部脉压处理。同时目标回波信号与参考信号的时延差和目标多普勒频率的变化,对去斜率数字脉压结果有一定的影响。该文通过理论分析和较全面的仿真,定量地分析了去斜率数字脉压中目标回波信号与参考信号时延差和多普勒频率的变化对数字脉压性能的影响,为工程应用中合理选择信号带宽、采样率和目标回波信号的时延提供了参考。     

基于偏时域相干算法的一种信号分析系统

本文提出将偏时域相干算法应用于一种实时信号分离系统，简要介绍了该系统的基本原理、系统的总体设计方案及该系统的适用条件．计算机仿真结果表明了该系统的有效性．