Carlos N. Bouza

Ranked set sub sampling the non response strata for estimating the difference of means

The existence of missing observations when the difference of means is estimated determines the need of sub sampling among the non respondents. Ranked set sampling is used for sub sampling. The information provided on one of the variables by the non respondents at the first attempt permits to rank them. The behavior of a ranked set sampling model with respect to other alternattives is studied in this paper. An unbiased estimator is derived and its expected variance is obtained. The proposed model is compared with the use of simple random sampling and Two-phase sampling for stratification.

Model‐Assisted Ranked Survey Sampling

The problem of Ranked Set Sampling [RSS] is analyzed and a ratio estimator is proposed. A simple linear regression superpopulation model is proposed as a counterpart to the design approach. A predictor is developed by using shrinkage techniques.

Double Sampling with Ranked Set Selection in the Second Phase with Nonresponse: Analytical Results and Monte Carlo Experiences

This paper is devoted to the study of the behavior of the use of double sampling for dealing with nonresponses, when ranked set sample is used. The characteristics of the sampling strategies are derived. The structure of the errors generated the need of studying of the optimality of the strategies by performing a set Monte Carlo experiments.

Estimating the population mean in the case of missing data using simple random sampling

In this paper, we suggest three new ratio estimators of the population mean using quartiles of the auxiliary variable when there are missing data from the sample units. The suggested estimators are investigated under the simple random sampling method. We obtain the mean square errors equations for these estimators. The suggested estimators are compared with the sample mean and ratio estimators in the case of missing data. Also, they are compared with estimators in Singh and Horn [Compromised imputation in survey sampling, Metrika 51 (2000), pp. 267–276], Singh and Deo [Imputation by power transformation, Statist. Papers 45 (2003), pp. 555–579], and Kadilar and Cingi [Estimators for the population mean in the case of missing data, Commun. Stat.-Theory Methods, 37 (2008), pp. 2226–2236] and present under which conditions the proposed estimators are more efficient than other estimators. In terms of accuracy and of the coverage of the bootstrap confidence intervals, the suggested estimators performed better than other estimators.

Optimal post-stratification for the study of the sustainability: An application to the monitoring of diversity in Sierra de Guerrero

The need of designing a monitoring network in Sierra de Guerrero motivated this paper. The study of the effect of deforestation of the forest needs of monitoring in the diversity. A quantitative evaluation of diversity is measured by estimating an index. Commonly the monitoring of biodiversity is based on the periodical selection of samples for evaluating the diversity. We propose to use sample information for determining post strata. They must constitute homogeneous zones in the forest. A stochastic program is developed for determining the post strata to be used for sampling. The procedure seems to be a good alternative with respect to the use of a heuristic procedure. The results presented are based on the data obtained in a research developed at one of the most important forest diversity reservoirs of Mexico

Study of the industrialization-ability of the production of mescal in Guerrero-Mexico

We considered the modeling of the evaluation of projects for industrializing the artisanal production of mescal. A Decision Support system is modeled for determining the priorities of the tasks. The ability for evaluating projects is considered. Data provided from a large research developed in Guerrero provided data for generating scenarios and evaluating behavior of the system.

The use of auxiliary information for solving non-response problems

SummaryThe unavailability of information from some sampled units complicates the use of current sampling methods. The classical solution is to select a subsample from within the non-respondents. A random non-response mechanism provides an alternative model within the randomization approach. A superpopulation point of view suggests use of a predictor. Shrinkage techniques are used to derive methods for dealing with non-responses. The accuracy of the analysed models is compared using Monte Carlo experiments.

Evaluacion de reglas de submuestreo para la estimacion de una diferencia en el caso de las no respuestas

ResumenLos resultados del uso de reglas de submuestreo para la estimación de la diferencia bajo la existencia de no respuestas se analizan tomando como base el error y el costo esperados. Criterios que permiten fijar cuándo una cierta regla es preferible se obtienen cuando el diseño es el muestreo simple aleatorio con reemplazo.AbstractThe results related with the use of subsampling rules for estimating the difference when there is nonresponse are analyzed by using the expectation of the error and the cost. Criteria that permit to fix the preference for a certain rule are obtained when simple random sampling with replacement is used.

Afijación del tamaño de muestra en estrategias p PXM-estratificadas bajo un modelo superpoblacional

SumarioEl problema de la afijación de los tamaños de muestra en estratos es abordado. Los sistemas de probabilidades desiguales se basan en una variable auxiliarXt. La existencia de un modelo superpoblacional permite el desarrollo de criterios de afijación óptima. Las propiedades de los tamaños de muestra obtenidos son similares a los clásicos.