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Coefficient of variation (CV) control charts are widely used to monitor processes in which the mean of process characteristic varies and its standard deviation changes with the mean. However, such ...

In recent years, the impact of measurement errors on the performance of various control charts have been well evaluated. However, as far as we know, the multiple sampling control charts in the lite...

Skip-lot sampling plans have the provision of inspecting only a fraction of lots, which reduces time and cost of the inspection. Thus, the skip-lot sampling plan is more cost-effective. The intenti...

Adapted from the acceptance sampling field, the double sampling monitoring schemes implement a two-stage strategy to decide whether the process being monitored is in-control or out-of-control. That...

Recent studies have shown that an adaptive T 2 chart with double sampling and variable sampling interval D S V S I T 2 chart shows a good performance in detecting small to moderate shifts in the me...

This study investigates the process for estimating the mean number of individuals having rare sensitive attribute in stratified random sampling as well as in stratified random double sampling using...

This article examines the zero numerator problem. This problem occurs when the misclassification rates are so low that both forms of misclassification may not both be present in the validation data. For this problem, the article compares two Bayesian methods for analyzing misclassified binary data that has a validation sub-study and three forms of a non-informative prior distribution. It shows that the two methods give similar results. However, the posterior distributions were sensitive to the choice of the prior distribution when misclassification rates are low. The article further presents a simulation study that reveals that the bias is small regardless of the considered prior distribution. However, when the misclassification rates are low, the coverage of credible intervals is markedly better for a Jeffreys’ prior than for either a Haldane’s or a uniform prior. Finally, the article highlights the merit of quantifying expert opinion to form a subjective prior distribution when the posterior distribution is sensitive to the prior.

In this paper, we design an innovative and general class of modified two-stage sampling schemes to enhance double sampling and modified double sampling procedures. Under the squared error loss plus...

In many applications, the quality of a process is characterized by the functional relationship between a response variable and one or more explanatory variables. This functional relationship is ref...

Control charts based on inspection with gauges are an interesting alternative to monitor quantitative variables when measurement is complex or expensive. The main advantage over variable control ch...

In statistical process monitoring (SPM), most of the monitoring schemes are designed assuming that the process parameters for the underlying distribution are known (i.e., Case K). In a variety of c...

This paper presents an adaptive T2 control chart for monitoring shifts in the mean vector of a multivariate normally distributed process. This chart which combines the double sampling, variable sam...

Chain-ratio estimators are often used to improve the efficiency of the estimation of the population total or the mean using two auxiliary variables, available in two different phases. An improved c...

Calibration approach is becoming more important in survey sampling. Calibration estimation helps in improving the estimates of population parameters by making use of auxiliary information. This pap...

To estimate the disease prevalence, a gold standard test is the best choice for accurate estimation. The gold standard could be very expensive or time consuming for use in practice. For this reason...

This study presents a double sampling (DS) np chart when the process parameter is estimated. The DS np chart is evaluated in terms of the average of the average run length and the standard deviatio...

This paper develops a new double sampling (DS) monitoring scheme, namely, the side-sensitive DS X¯ chart, to monitor the process mean. The operational procedure is presented first followed by the e...

The quality loss suggested by Taguchi has been recognised as a new quality evaluation based on variable property instead of the quality evaluation based on traditional attribute property such as th...

A flexible scrambled response model using a randomization device for quantitative sensitive data is used to evaluate the protection of respondents’ privacy. A double-sampling regression-cum-exponen...

This manuscript presents the process for estimating the mean number of individuals having rare sensitive characteristic when population units are heterogeneous with and without prior information on the supplementary (unrelated rare non-sensitive) characteristic. The rare stigmatized parameter is estimated using an ameliorated two-stage randomized response model under stratified sampling and stratified double sampling schemes. The properties of the suggested estimators have been discussed under random, proportional and optimal allocations of sample from different strata. The proposed estimators perform better over some contemporary competent estimators for similar situations which have been shown through empirical studies.

Acceptance sampling plans are quality tools for the manufacturer and the customer. The ultimate result of reduction of nonconforming items will increase the profit of the manufacturer and enhance t...

An economic-statistical design of the synthetic double sampling (synDS) T2 chart is presented in this study. The cost function is minimized to obtain the optimal design parameters of the synDS T2 c...

The present article deals with the estimation of mean number of respondents who possess a rare sensitive character in presence of known and unknown proportion of a rare unrelated non-sensitive attribute by using the Poisson probability distribution in stratified random sampling as well as in stratified random double sampling. The variance of rare sensitive character is also derived under proportional and optimal allocation methods in stratified random sampling when stratum sizes are known and unknown. The properties of the suggested estimation procedures have been deeply examined. The proposed model is found to be dominant over Lee et al. [Estimation of a rare sensitive attribute in a stratified sample using Poisson distribution. Statistics. 2013;47:575–589] model. Numerical illustrations are presented to support the theoretical results. Results are analysed and suitable recommendations are put forward to the survey practitioners.

The purpose of this paper is to investigate the economic and economic statistical designs of the synthetic double sampling (DS) X‾ chart. The optimal design parameters for the economic design are d...

In this article, we propose a method of planning and determining the optimum parameters of a SkSP-R skip-lot sampling plan by using the attribute double sampling plan as the reference plan. The SkSP-R plan is a new type of skip-lot sampling plan which has a provision for re-inspecting the submitted lots. The optimal plan parameters of the suggested sampling plan are estimated with the target that the average sample number be minimized and satisfying both the specified producer's as well as the consumer's risks simultaneously. In order to obtain the optimum parameters, tables are also built for different combinations of the acceptable quality level and the limiting quality level in conjunctions with different producer's and consumer's risks. An illustrative example is provided for the implementation of the suggested plan. The advantages of the suggested plan over the existing conventional sampling plans and other existing skip-lot sampling plans are also described.

A combined double sampling and variable sampling interval (DSVSI) np chart is investigated in this study. The optimal design of the DSVSI np chart is based on minimizing the out-of-control average time to signal. From the numerical results, the DSVSI np chart performs reasonably well in comparison with the standard np chart, double sampling np chart, synthetic double sampling np chart and other existing np type control charts for detecting increases in the process of fraction non-conforming, based on the zero-state case. An example is provided to illustrate the application of the DSVSI np chart.

Accept on zero and accept on one sampling plans are two common approaches to determine if a manufacturing lot can be accepted or rejected. Accept on zero plans inspect fewer items than the accept on one plans. On the other hand, accept on one plans have a higher probability of accepting a lot when the defect rate is between the Acceptable and Rejectable Quality Levels. This article proposes a double sampling plan whose probability of accepting a lot resembles an accept on one plan yet inspects considerably fewer items on average.

This study proposes a double sampling (DS) Max chart for monitoring shifts in the process mean and standard deviation. The design of the DS Max chart depends on five parameters, i.e. first and seco...

This paper addresses the problem of estimating the population variance S2y of the study variable y using auxiliary information in sample surveys. We have suggested a class of estimators of the population variance S2y of the study variable y when the population variance S2x of the auxiliary variable x is known. Asymptotic expressions of bias and mean squared error (MSE) of the proposed class of estimators have been obtained. Asymptotic optimum estimators in the proposed class of estimators have also been identified along with its MSE formula. A comparison has been provided. We have further provided the double sampling version of the proposed class of estimators. The properties of the double sampling version have been provided under large sample approximation. In addition, we support the present study with aid of a numerical illustration.

Semi-competing risks data arise when two types of events, non-terminal and terminal, may be observed. When the terminal event occurs first, it censors the non-terminal event. Otherwise the terminal event is observable after the occurrence of the non-terminal event. In practice, it can be hard to ascertain all terminal event information after the non-terminal event. Yu and Yiannoutsos [(2015), ‘Marginal and Conditional Distribution Estimation from Double-Sampled Semi-Competing Risks Data’, Scandinavian Journal of Statistics, 42, 87–103] considered a setting when the terminal event is ascertained via double sampling from only a subset of patients who experienced the non-terminal event. They discussed estimation for marginal and conditional distributions under this double sampled semi-competing risk data framework. We propose a more efficient estimation method in the same setting by fully utilising the non-terminal event information. The efficiency gain can be substantial as observed in our simulatio...

This study proposes a synthetic double sampling s chart that integrates the double sampling (DS) s chart and the conforming run length chart. An optimization procedure is proposed to compute the optimal parameters of the synthetic DS s chart. The performance of the synthetic DS s chart is compared with other existing control charts for monitoring process standard deviation. The results show that the synthetic DS s chart is more effective for detecting increases in the process standard deviation for a wide range of shifts. An example is provided to illustrate the operation procedure of the synthetic DS s chart.

We suggested the class of estimators of the population mean with its bias and mean square error. It has been shown that the suggested class is more efficient than the usual unbiased, ratio, product and regression estimators and estimators due to Bahl and Tuteja (1991), Singh et al. (2009), and Upadhyaya et al. (2011). In addition an empirical study also carried out to and founded that the members of suggested family also have improvement over Grover and Kaur (2011) and Shabbir and Gupta (2011) classes. Two-phase (double) sampling version of the proposed class was also given.

SYNOPTIC ABSTRACTA Bayesian approach is considered for a point and interval estimation for odds ratios of two binomial proportion parameters using double-sampling data subject to false-positive misclassification. For such data, we derive an easy-to-implement, closed-form algorithm for drawing from the posterior distributions. Application of this algorithm is illustrated using data collected about student laboratory grades from a course.

This paper proposes useful exact bounds for the parameters of the double sampling S2 chart with known process variance and it also investigates the properties of the double sampling S2 chart with e...

In this article, a new attributes double sampling plan for three-class products (ADSPTP) is presented, and the corresponding operating characteristic function is constructed based on the given procedure of performing ADSPTP. Average sample numbers (ASN) for complete inspection and curtailed inspection of the second sample are derived and the extreme point is discussed on the three-dimensional ASN surface. In addition, the differences arising from different parameters are studied. Sampling plans are designed by a nonlinear optimization model. Finally, numerical examples and discussions are given to illustrate the obtained results, and tables of the designed plans under various conditions are provided.

In this paper, we introduce a version of Hayter and Tsui's statistical test with double sampling for the vector mean of a population under multivariate normal assumption. A study showed that this new test was more or as efficient than the well-known Hotelling's T2 with double sampling. Some nice features of Hayter and Tsui's test are its simplicity of implementation and its capability of identifying the errant variables when the null hypothesis is rejected. Taking that into consideration, a new control chart called HTDS is also introduced as a tool to monitor multivariate process vector mean when using double sampling.

This paper proposes a side-sensitive group runs double sampling (SSGRDS) chart to detect shifts in the process mean. It improves the side-sensitive group runs chart proposed by Gadre and Rattihalli. The implementation of the SSGRDS chart is explained. The newly developed SSGRDS chart is compared with the synthetic, double sampling, synthetic double sampling, side-sensitive group runs and exponentially weighted moving average charts, in terms of the zero-state and steady-state average number of observations to signal (ANOS) and expected average number of observations to signal (EANOS). The zero-state and steady-state ANOS (ssANOS) and EANOS results reveal that the optimal SSGRDS chart generally performs well for detecting small and large mean shifts, from an overall perspective, compared with the optimal versions of other competing charts. This article provides tables of optimal charting parameters to facilitate the design of the SSGRDS chart. From these tables, the user can directly determine the optimal ...

The synthetic double sampling (SDS) X chart comprises the double sampling (DS) X and conforming run length (CRL) sub-charts. The SDS X chart has been studied under the assumption of known process parameters in the literature. Nevertheless, in practice, process parameters are usually unknown and are estimated from an in-control Phase I dataset. This paper investigates the performance of the SDS X chart with estimated process parameters, in terms of the average run length (ARL), average number of observations to signal (ANOS) and standard deviation of the run length (SDRL). The performance of the SDS X chart with estimated process parameters by minimizing the out-of-control ARL and the out-of-control ANOS is compared with the corresponding chart’s performance with known process parameters. In addition, the minimum number of Phase I samples required by the SDS X chart with estimated process parameters so that it has approximately the same in-control ARL and ANOS performances as the chart with k...

A combination of double sampling and variable sampling interval (DSVSI) charts can increase the efficiency of signaling small shifts . This study proposes an economic-statistical model for designing joint DSVSI and s charts. The proposed approach uses the economic model developed by Duncan in 1956. Research results indicate that the economic-statistical design of the joint DSVSI and s charts outperformed traditional economic design approach in detection abilities of process shifts; variable cost (a2), expected costs resulting from defective products when the process was in control (C0), and the expected number of assignable causes (λ) have the major influence on cost E(C′); deviations (δ, γ) significantly influenced cost E(C′); and statistical limitations () do not substantially affect cost E(C′).

Bayesian acceptance sampling plans, which utilize prior information on the process variation, can be employed as an alternative to conventional types of plans for taking decisions on the disposition of submitted lots. A special type of double sampling inspection plans by attributes with small acceptance numbers using Bayesian methodology is presented in this paper emphasizing its significance over small acceptance number single sampling plans. The procedures for designing such sampling plans for specified degree of discrimination which would ensure protection to the producer and consumer are discussed with illustrations under the conditions for the application of gamma-Poisson distribution.

Detectability issues create uncertainty in field surveys of animal and plant populations. Detectability correction is one method employed to deal with this problem when there is reasonable certainty that detectability is roughly constant with time or in different areas. Two new reduced-variance estimators of detectability are introduced and evaluated for the case of using a detectability correction for new areas that are surveyed only once. The new estimates are unbiased or nearly unbiased and produce population estimates with smaller variance than the Lincoln–Petersen estimate.

Investigating the prevalence of a disease is an important topic in medical studies. Such investigations are usually based on the classification results of a group of subjects according to whether they have the disease. To classify subjects, screening tests that are inexpensive and nonintrusive to the test subjects are frequently used to produce results in a timely manner. However, such screening tests may suffer from high levels of misclassification. Although it is often possible to design a gold-standard test or device that is not subject to misclassification, such devices are usually costly and time-consuming, and in some cases intrusive to the test subjects. As a compromise between these two approaches, it is possible to use data that are obtained by the method of double-sampling. In this article, we derive and investigate four test statistics for testing a hypothesis on disease prevalence with double-sampling data. The test statistics are implemented through both the asymptotic method suitable for large samples and approximate unconditional method suitable for small samples. Our simulation results show that the approximate unconditional method usually produces a more satisfactory empirical type I error rate and power than its asymptotic counterpart, especially for small to moderate sample sizes. The results also suggest that the score test and the Wald test based on an estimate of variance with parameters estimated under the null hypothesis outperform the others. An real example is used to illustrate the proposed methods.

In this paper, we consider the Birnbaum–Saunders distribution as a life model to develop various acceptance sampling schemes based on the truncated life tests. We develop the double sampling plan and determine the design parameters satisfying both the producer's and consumer's risks simultaneously for the specified reliability levels in terms of the mean ratio to the specified life. We also propose a group sampling plan and determine the parameters by the above-mentioned two-point method. Tables are constructed for the proposed sampling plans and results are explained with examples.

This article presents the calibration procedure of the two-phase randomized response (RR) technique for surveying the sensitive characteristic. When the sampling scheme is two-phase or double sampling, auxiliary information known from the entire population can be used, but the auxiliary information should be information available from both the first and second phases of the sample. If there is auxiliary information available from both the first and second phases, then we can improve the ordinary two-phase RR estimator by incorporating this information in the estimation procedure. In this article, we used the new two-step Newton's method for computing unknown constants in the calibration procedure and compared the efficiency of the proposed estimator through some numerical study.

In this article, we introduce minimum divergence estimators of parameters of a binary response model when data are subject to false-positive misclassification and obtained using a double-sampling plan. Under this set up, the problem of goodness-of-fit is considered and divergence-based confidence intervals (CIs) for a population proportion parameter are derived. A simulation experiment is carried out to compare the coverage probabilities of the new CIs. An application to real data is also given.

A common approach to the design of an acceptance sampling plan is to require that the operating characteristic (OC) curve should pass through two designated points that would fix the curve in accordance with a desired degree of discrimination. This paper presents a search procedure for the selection of double sampling inspection plans of type DSP - (0, 1) for specified two points on the OC curve, namely acceptance quality limit, producer's risk, limiting quality and consumer's risk. Selection of the plans is discussed for both the cases of fraction non-conforming and the number of non-conformities per unit.

The design of a sampling inspection plan that involves the minimum average total inspection at a given quality level is of practical interest. The acceptance sampling literature suggests that a specific type of double sampling plan be used for this purpose. This double sampling plan allows no non conforming units in the first stage and no more than one non conforming unit in the second stage of inspection. In this note it is argued that the zero acceptance number single sampling plan is still preferred to a double sampling plan for achieving minimum average total inspection at a given point on the Operating Characteristic (OC) curve. A theoretical discussion on the broken sample size is provided for justifying the choice of the single sampling plan.

In this paper, a new sampling scheme called the 'conditional double sampling scheme' (CDSS) has been proposed. A compact table is presented for the selection of a CDSS indexed by various combinations of entry parameters. Advantages of the CDSS over the single sampling scheme have been discussed. The basis for the construction of the table is given.

Transect relascope sampling is a recently proposed method for making efficient inventories of coarse woody debris on the ground. However, before the method can be recommended, its performance in the field requires investigation. This paper presents the results of a field study in which 11 surveyors tested the method in two coniferous stands in northern Sweden. The average bias introduced by the surveyors was moderate under normal sighting conditions, but underestimation was substantial when combining a small relascope angle with poor sighting conditions. In all cases, the differences between the systematic errors of individual surveyors were substantial. The conclusion is that transect relascope sampling is not an appropriate method when the demand for unbiased estimates is high, e.g. in connection with long-term monitoring, but that the method can be useful as a first phase in double sampling or in ocular-based inventories aimed at identifying biologically valuable areas.