规模以下工业抽样框要加强分层标志的维护

规模以下工业抽样框的分层标志是工业总产值（营业收入），标志值的变化将影响分层、层内离差、样本单位数，最终影响抽样推算精度。我们确定抽样方案后，是假定抽样框按某一趋势平稳变化的，这个假定条件与现实有较大差异，因此，必须加强工业总产值（营业收入）的审核和维护。 一、影响工业总产值（营业收入）变化的原因 １．企业自身的发展变化引起工业总产值（营业收入）的增大或减少。这一因素引起的变化通常有比较稳定的趋势，因为在较短的生产周期（比如一年）内，在经济环境相对稳定的情况下，工业生产不会出现大的波动。 ２．填报…     

不完全涵盖抽样框对规模以下工业抽样调查的误差影响

本文分别论述了造成规模以下工业抽样框"不完全涵盖"的客观原因和人为因素,并对此造成的非抽样误差进行量化分析;最后提出了解决抽样框的"不完全涵盖"问题的两点理论思路。     

对规模以下工业抽样框清查维护的探讨

黑河市规模以下工业抽样调查工作已实施四个年头。在抽样调查工作中,我们认为搞好企业抽样框清查、完善及维护是做好抽样调查工作的基础和关键。 一、建立、健全抽样清查建框工作制度 对规模以下工业企业抽样清查建框,应属全面调查,类似一次小型普查,调查涉及的范围广、工作量大、时效性强,所花费的人力、物力、财力多,组织工作复杂繁重,故不宜经常进行。所以目前进行的一年一次清查建框维护工作在操作上是可行的,应用上是合理的。为了能在有限     

规模以下工业抽样调查审核的做法

如何提高以市（地）为总体的规模以下工业抽样调查数据质量？我们结合工作实践，进行了一些探索，主要做法是分阶段把关，全程搞监控。 抽样框是抽样调查的基础。其质量高低直接关系到整个抽样调查工作的成败。为此，我们要求各市（地）在每次上报年报和定报之前都要对抽样框进行清查与维护，使抽样框真实、可靠。我们的做法：各地将抽样框维护形式、方法、结果等以书面形式上报省企调队产业处。省企调队重点审核上报抽样框是否有空记录，是否与本次调查规定的字段结构、宽度等一致。目录抽样框中新旧企业周性的个数之和是否等于上报个数，…     

规模以下工业抽样设计研究

为推动规模以下工业抽样调查工作以及解决当前调查面临的有关问题,本文对抽样设计进行了改进研究。首先,本文对规模以下工业抽样设计演变过程进行系统梳理,总结了现行抽样设计充分利用双重抽样框设计和综合运用三种抽样方法的特点。其次,针对园区层企业密度高的特点,探索结合园区因素改进地域抽样设计,对园区层和非园区层分别抽样,解决调查中面临的非抽样误差问题,并调整辅助变量使其与核心指标相关性均较高,确保抽样推断精度,有效提高抽样调查效率。并以我国东 部某省为例进行实证模拟得到结合园区因素抽样设计对调查工作改进的结论。再次,针对我国各级政府管理需要以及局队业务分工优化调整情况,介绍了规模以下工业样本追加理论和实证应用的主要研究成果。最后,在大数据时代数据来源广泛的背景下,本文在多重抽样框设计以及利用辅助变量提升样本轮换推断精度方面提出了进一步改进抽样设计的思路。     

规模以下工业抽样调查“三级”抽样方法探索

以省为总体的规模以下工业抽样调查工作经过三年多的实践已取得了成功。如何将此项工作推至市、县两级 ,以满足省、市、县三级GDP核算的需要 ,当务之急是研究制订一个科学、高效、切实可行的规模以下工业“三级”抽样设计方案。本文通过“自上而下”和“自下而上”两种三级抽样方法的设计并实证分析 ,适时提出了我省规模以下工业“三级”抽样方法的操作模式     

基于双重抽样框的抽样估计方法研究

 随着经济社会的快速发展,抽样调查中调查对象的流动日益频繁,传统的单一抽样框很难完整覆盖流动性的目标总体,如果一定要使单一抽样框实现完整覆盖,成本必定是高昂的,甚至由于编制过程漫长使抽样调查失去其时效性。有时采用两个不完整抽样框的组合可以实现对目标总体的完整覆盖。基于双重抽样框进行抽样调查,其抽样设计工作不难,但是由于样本在两个抽样框中存在交叉,致使抽样估计甚是困难。基于此,本文将系统评述目前国外已有的各种双重抽样框估计方法,将这些方法分为分离抽样框估计和组合抽样框估计两类,并按照统一的模式比较各估计方法的功效,文章最后对我国采用双重抽样框调查进行展望。     

Two-stage cluster sampling with hybrid ranked set sampling in the secondary sampling frame

In surveys of natural resources in agriculture, ecology, fisheries, forestry, environmental management, etc., cost-effective sampling methods are of major concern. In this paper, we propose a two-stage cluster sampling (TSCS) in integration with the hybrid ranked set sampling (HRSS)—named TSCS-HRSS—in the second stage of sampling for estimating the population mean. The TSCS-HRSS scheme encompasses several existing ranked set sampling (RSS) schemes and may help in selecting a smaller number of units to rank. It is shown both theoretically and numerically that the TSCS-HRSS provides an unbiased estimator of the population mean and it is more precise than the mean estimators based on TSCS with SRS and RSS schemes. An unbiased estimator of the variance of the proposed mean estimator is also derived. A similar trend is observed when studying the impact of imperfect rankings on the performance of the TSCS-HRSS based mean estimator.     

Economic design of continuous sampling plan under linear inspection cost

The article explores the problem of an economically based type I continuous sampling plan (CSP-1 plan) under linear inspection cost. By assuming that the per unit inspection cost is linearly proportional to the average number of inspections per inspection cycle, and by solving the modified Cassady et al.'s model, we not only have the required level of product quality but also obtain the minimum total expected cost per unit produced.     

Calibration estimator of population mean under stratified ranked set sampling design

Calibration method adjusts the original design weights to improve the estimates by using auxiliary information. In this article we have proposed new calibration estimators under stratified ranked set sampling design and derive the estimator of variance of calibration estimator. A simulation study is carried out to see the performance of proposed estimators.     

Bounded risk estimation of linear combinations of the location and scale parameters in exponential distributions under two-stage sampling

Two-stage sampling is proposed for estimating linear combinations of the location and scale parameters of exponential distributions with bounded quadratic risk functions. Exact formulae for the expected values and risks of the estimators are derived, and the performance of estimators is studied. Illustrations with real data are included.     

Parametric estimation of location and scale parameters in ranked set sampling

This paper develops parametric inference for the parameters of location-scale family of distributions based on a ranked set sample. Likelihood function incorporates within-set ranking errors into the model through a missing data mechanism. The maximum likelihood estimators of the location-scale and missing data model parameters are constructed and an EM-algorithm is provided. It is shown that the proposed estimator is robust against imperfect ranking error and provides higher efficiency over its competitors.     

对分层抽样设计的改进

 在社会经济研究中,由于实际条件的限制,往往采用抽样调查的方法获得的现象总体的信息,当总体内部差异比较大时,应首先对总体个单位按有关指标加以分层,然后再从各层中按随机原则抽选一定单位构成样本。分层可以大大提高抽样推断的精度,降低工作量和成本,所以实际工作中分层抽样得到了广泛的应用。 样本分配是分层抽样研究的一个重要方面。影响样本分配的因素主要有：各层方差、各层样本单位数、调查成本等,其中调查成本是与实际工作有密切影响的因素。当存在多个项目场合中调查成本与调查精度之间的函数关系,为实际工作中的多目标决策提供思路。     

Model and design correspondence in finite population sampling

A correspondence rule is suggested for the choice of a sampling design when prior knowledge concerning a finite population is available. Designs satisfying the correspondence rule are discussed in the case of random permutations models. A general optimality theorem is given for strategies under such models. Approximate correspondences satisfied by systematic sampling and πps sampling are also indicated.     

Change of origin and scale in ratio and difference methods of estimation in sampling

This paper discusses two estimators of the mean of a finite population based on a simple random sample from it, when supplementary information on a variable positively correlated with the variable of interest is available. Simultaneous reductions in absolute bias and mean square error of the estimator are seen as compared with those of the traditional estimator in the ratio method of estimation. The suggested estimators are simple for computation and there is no appreciable increase in the cost as well.     

Two-step calibration of design weights in survey sampling

ABSTRACT

In this article, a new two-step calibration technique of design weights is proposed. In the first step, the calibration weights are set proportional to the design weights in a given sample. In the second step, the constants of proportionality are determined based on different objectives of the investigator such as bias reduction or minimum mean squared error. Many estimators available in the literature can be shown to be special cases of the proposed two-step calibrated estimator. A simulation study, based on a real data set, is also included at the end. A few technical issues are raised with respect to the use of the proposed calibration technique: both limitations and benefits are discussed.     

Non-rejective implementations of the Sampford sampling design

Sampford sampling is a method for unequal probability sampling. There exist several implementations of the Sampford sampling design which all are rejective methods, i.e. the sample is not always accepted. Thus the existing methods can be time consuming or even infeasible in some situations. In this paper, a fast and non-rejective list-sequential method, which works in all situations, is presented. The method is a modification of a previously existing rejective list-sequential method. Another list-sequential implementation of Sampford sampling is also presented.