On the estimation of population variance using auxiliary attribute in absence and presence of non-response

In this article we proposed a new class of estimators for estimating thefinite population variance using available auxiliary attribute in absence and presence of non-response problem. Properties such as bias and mean square error of the proposed class are derived up to the first order of approximation. The proposed class is more efficient than the Singh et al. (1988), Shabbir and Gupta (2007), Singh and Solanki (2013a), usual sample variance and regression estimators

Efficient control chart-based monitoring of scale parameter for a process with heavy-tailed non-normal distribution

Statistical process control is a procedure of quality control that is widely used in industrial processes to enable monitoring by using statistical techniques. All production processes are faced with natural and unnatural variations. To maintain the stability of the production process and reduce variation, different tools are used. Control charts are significant tools to monitor a production process. In this article, we design an extended exponentially weighted moving average (EEWMA) chart under the assumption of inverse Maxwell (IM) distribution, an IM EEWMA (IMEEWMA) control chart. We have estimated the performance of the proposed chart in terms of various run-length (RL) properties, including the average RL, standard deviation of the RL and median RL. We have also carried out a comparative analysis of the proposed chart with the existing Shewhart-type chart for IM distribution (VIM chart) and IM exponential weighted moving average (IMEWMA) chart. We observed that the proposed IMEEWMA chart performed better than the VIM chart and IMEWMA chart in terms of the ability to detect small and moderate shifts. To demonstrate its practical application, we have applied the IMEEWMA chart, along with existing control charts, to monitor the lifetime of car brake pad data. This real-world example illustrates the superiority of the IMEEWMA chart over its counterparts in industrial scenarios

poblacional en muestreo de encuestas

In this paper, generalized exponential-type estimator has been proposed for estimating the population variance using mean auxiliary variable in singlephase sampling. Some special cases of the proposed generalized estimator have also been discussed. The expressions for the mean square error and bias of the proposed generalized estimator have been derived. The proposed generalized estimator has been compared theoretically with the usual unbiased estimator, usual ratio and product, exponential-type ratio and product, and generalized exponential-type ratio estimators and the conditions under which the proposed estimators are better than some existing estimators have also been given. An empirical study has also been carried out to demonstrate the efficiencies of the proposed estimators

Generalized Class of Variance Estimators under Two-Phase Sampling for Partial Information Case

This paper considers a class of generalized estimators for estimating the unknown population variance using two auxiliary variables when mean of one auxiliary variable may not be available. The expressions for bias and mean square error of the proposed estimators are obtained up to the first order of approximation. Conditions for which the proposed generalized estimator is more efficient than the existing estimators have been derived. Both empirical and simulation studies have also been carried out to analyze the efficiency of the proposed estimators with some existing estimators

An exponential and log ratio estimator of population mean using auxiliary information in double sampling

In this study an improved version of ratio type exponential estimator is been proposed for estimating average of study variable when the population parameter(s) information of second auxiliary variable is available. The proposed estimator compared with usual unbiased estimator and conventional ratio estimators numerically and hypothetically. The mean square error is also obtained and checked the efficiency of the proposed estimator with usual ratio, Singh and Vishwakarma (2007), Singh et al. (2008), Noor-ul-Amin and Hanif (2012), Yadav et al. (2013) and Sanaullah et al. (2015) estimators

A multivariate regression-cum-exponential estimator for population variance vector in two phase sampling

In this study we have proposed a multivariate regression-cum-exponential type estimator for estimating a vector of population variance. In the present study, unknown population variance vector estimation has been discussed using multi-auxiliary variables in two-phase sampling and different cases have also been derived. A comparison between existing and the proposed multivariate, bivariate and univariate estimators has been prepared with the help of a real data for estimating population variance. A simulation study for multivariate estimator using multi-auxiliary variables has also been carried out to demonstrate the performance of the estimators. Keywords: Multivariate estimator, Multi-auxiliary variables, Two-phase sampling, Regression estimator, Variance-covariance matrix, Simulatio

Generalized exponential type estimator for population variance in survey sampling

En este artículo, de tipo exponencial generalizado ha sido propuesto conel fin de estimar la varianza poblacional a través de una variables auxiliaren muestreo en dos fases. Algunos casos especiales del estimador medio yel sesgo del estimador generalizado propuesto son derivados. El estimadores comprado teóricamente con otros disponibles en la literatura y las condicionesbajos los cuales éste es mejor. Un estudio empírico es llevado a cabopara comprar la eficiencia de los estimadores propuestos