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The authors develop the estimation of the difference of means of a pair of variables X and Y when we deal with missing observations. A seminal paper in this line is due to Bouza and Prabhu-Ajgaonkar when the sample and the subsamples are selected using simple random sampling. In this this chapter, the authors consider the use of ranked set-sampling for estimating the difference when we deal with a stratified population. The sample error is deduced. Numerical comparisons with the classic stratified model are developed using simulated and real data.

We propose a model for several alternative approaches to the prediction of the probabilities involved by processing the obtained signals sent by the players, which may be companies competing in the market. They set a minimum level of expected utility and are interested in the probability that this expectation will be satisfied. These approaches are analyzed using Monte Carlo experiments, developed in the framework of Game Theory and different statistical models to make predictions about the probability of success or to obtain a certain utility. The behavior of the different proposed strategies is established, considering that the errors follow a Normal, double Exponential and Cauchy distribution. A comparison is made of the results given by the algorithms programmed R and SAS, finding that R are better in terms of, however GLIMIX PRC MIXED of SAS has lower values of V2 in all cases. RESUMEN Se propone un modelo para varios enfoques alternativos de la predicción de las probabilidades involucradas a partir de procesar las señales obtenidas enviadas por los jugadores, que pueden ser empresas compitiendo en el mercado. Ellos fijan un nivel mínimo de la utilidad esperada y se interesan en la probabilidad de que se satisfaga esta expectativa. Estos enfoques son analizados usando experimentos de Monte Carlo, desarrollado en el marco de la Teoría de Juegos y diferentes modelos estadísticos para hacer predicciones sobre la probabilidad de éxito o de obtener una cierta utilidad. Se establece el comportamiento de las distintas estrategias propuestas considerando que los errores siguen una distribución normal, doble exponencial y Cauchy. Se hace una comparación de los resultados dados por los algoritmos programados el R y SAS, encontrando que son mejores los de R en términos de, sin embargo GLIMIX PRC MIXED de SAS tiene valores menores de V2 en todos los casos.

In this chapter, we suggest an improved form of exponential ratio and product estimators using ranked set sampling in order to estimate the population mean Y ¯ of study variate Y using auxiliary variate X . The mean-squared error of the proposed class of estimators is obtained. To judge the merits of the suggested estimators over others a simulation study has been carried out.

In the field of sampling, researchers have paid attention to proposing estimators for unknown population mean using auxiliary information. In many instances, in place of auxiliary information, information is available in the form of an auxiliary attribute. In this chapter an effort has been made to review the work related to the estimation problem using auxiliary attribute information.

In the field of sampling, researchers have paid attention to proposing estimators for unknown population means using auxiliary information. In many instances, in place of auxiliary information, information is available in the form of an auxiliary attribute. In this chapter, the work related to estimation problems using auxiliary attribute information is reviewed.

We consider the problem of estimating the mean of a sensitive quantitative variable Y. The seminal work of Warner (1965) on randomized response has motivated the development of a fruitful theory. Gupta-Thornton (2002) proposed a method for scrambling the sensitive variable using an auxiliary variable X of known distribution. We propose using this distribution for generating order statistics. This chapter is concerned with the development of alternative scrambling procedures, which use order statistics of X. A comparison is developed in terms of the variance of the involved estimators.

Ranked set sampling is considered as a design for selecting a simple from a finite population. Generally it performs better than simple random sampling. Chen et al. (2006) proposed a procedure for ranking categorical variables. This paper is concerned with the study of a sensitive variable. The randomized responses procedure due to Warner (1965) is used for eliminating answer biases. The variance of the proposed estimator is derived and it is larger than the proposal of Chen et al. (2006). A study of the quality of the environment is developed. Direct responses and randomized response estimators are compared. Ranking procedures used information provided by measurements of the contaminants in the air and water.

In many medical researches, it is needed to determine the optimal sample size allocation in a heterogeneous population. This paper proposes the algorithm for optimal sample size allocation. We consider the optimal allocation problem as an optimization problem and the solution is obtained by using Bisection, Secant, Regula–Falsi and other numerical methods. The performance of the algorithm for different numerical methods are analyzed and evaluated in terms of computing time, number of iterations and gain in accuracy using stratification. The efficacy of algorithm is evaluated for the response in terms of body mass index (BMI) to the dietetic supplement with diabetes mellitus, HIV/AIDS and cancer post-operatory recovery patients.

Derivatives play an important role in social and economic studies. They describe the behavior of conditional expectations. Once a phenomena is characterized by parametric specifications, the conditional expectation m(x) may be modeled by a regression function. Then, derivatives may be computed by fitting the regression function. In applications, parametric estimators are commonly used, because of the un-knowledge of other more effective methods. The validity of a regression fitting approach depends on the knowledge of certain aspects related with the true functional form. In this paper, we develop a study on the usage of soft computing methods for providing an alternative to the use of non-parametric regression. We develop our modeling including neural networks and rough sets approaches. The studied problem is the eutrophication due to the growth of the population of algae. Real life data is provided by a study on a fresh water basin. They are used for developing a comparison of different approaches. A methodology is recommended for implementing a monitoring system of the water quality.

Two Randomized Response sampling models are developed using the scrambling procedure proposed by Ryu-Kim-He-Park are developed. At F rst we consider the RaoHartleyCochran (RHC) strategy and the estimators of the means is developed. Afterwards Ranked Set Sampling (RSS) design is used and te correpsondign estimators is obtained. The corresponding variances are derived and the eK iciency of RSS against RHC procedure is studied.

10.12957/cadest.2013.15772We consider the modified ratio estimator proposed by Swain (2013). It is an extension of the classic ratio estimator. The objective of this paper is developing the ranked set counterpart of the new estimator, developed by Swain (2013). We derived a new ranked set sampling ratio estimator. For illustrating the behavior of the proposal a comparison of their approximate mean squared error was developed. The proposed procedure appeared as more accurate. Empirical studies give an insight on the magnitude of the efficiency of the estimator developed.

Missing data is a well-recognized problem which arises in statistical inferences and data analysis. We address different possible ways to handle missing data, to ameliorate its effect on the reliability and accuracy of survey-based inferences. Subsampling the non-respondents and imputation of missing values, are considered as methods for dealing with non-responses. This book presents the work developed on Ranked Set Sampling (RSS) in dealing with missing data. RSS is a relatively new sampling design. This chapter may be considered as an introduction to the rest of the oeuvre.

We may consider the existence of missing observations as unimportant, considering that the risk of misunderstanding is negligible. The surveyor assumes some model that allows adequately explaining the variable of interest. In such cases, we are able to predict the unknown values and to plug them into some estimator. Generally, the models used for imputing in sampling are not complicated and rely on simple ideas. Imputation in simple random sampling has been developed for decades; the literature is increased yearly. Ranked Set Sampling (RSS) alternatives are presented in this chapter. The efficiency of this approach is supported for the different models. On some occasions the preference of RSS is doubtful and needs numerical comparisons.

Simple random sampling is the kernel of sampling theory. The basic theory of statistical inference is supported by the assumption of using samples selected by means of this design. During the last decade Ranked Set Sampling has appeared as a challenge to this design. It is implemented by selecting units with replacement and the sampled units are ordered (ranked). Each order statistic is observed once. This process can be repeated if needed to observe various realizations of each order statistic. A review of the most significant results is developed in this chapter, taking into account the modeling of missing data.

The superiority of Ranked Set Sampling (RSS) models is measured by the comparison of the Mean Square Errors of the models with respect to their alternatives. The expressions support general evaluations of the gains in accuracy but their values depend on the underlying distribution or the characteristics of the studied population. We present some numerical studies for illustrating the behavior of RSS strategies.

This paper presents a brief demonstration of Scholz’s third conjecture [1] for n numbers such that their minimum chain addition is star type [2]. The demonstration is based on the proposal of an algorithm that takes as input the star-adding chain of a number n, and returns a string in addition to x = 2n - 1 of length equal to l (n) + n - 1. As for any type addition chain star of a number n, this chain is minimal demonstrates the Scholz’s third Conjecture for such numbers.

La preferencia de sistemas de probabilidades al utilizar estrategias poissonianas es analizada utilizando como criterio la exactitud de los estimadores. Para ello se utiliza un modelo superpoblacional y se obtienen los criterios de preferencia dentro de esta clase de estrategias.

Se realiza un estudio de cómo los turistas que acuden a Acapulco valoran las categorías autorrealización y autoconcepto. Estas juegan un papel importante en la valoración del uso del tiempo libre y la satisfacción. Este estudio fija la importancia de indicadores y su interrelación a partir de estudiar los datos suministrados por una muestra de 399 turistas. Los resultados obtenidos permiten identificar en que aspectos se debe trabajar para mejorar la satisfacción de los turistas para tener un mejor desempeño de este destino en el mercado turístico.

[Resumen] A partir del uso de índices de satisfacción del cliente (Consumer Satisfaction Index) se han erigido diversas metodologías para evaluar el desempeño de los hoteles. El interés primal es considerar diversos atributos y servicios y como estos conforman la satisfacción de los clientes. Dada la naturaleza del problema la población bajo estudio es dinámica. De hecho lo más usual es que la recolección de información deba ser considerada como de naturaleza censal. En algunos casos esta es complementada por encuestas especialmente diseñadas. Esta situación establece que los índices no son analizables utilizando métodos estadísticos inferenciales. Solo se puede hacer uso de métodos descriptivo y valerse de la modelación moderna para hacer análisis coherentes. Consideramos la posibilidad de que el gerente pueda aceptar la validez de un cierto modelo superpoblacional. Se justifica como entonces es posible hacer estudios utilizando métodos como los de Componentes. Se ilustra lo discutido al hacer un estudio de las cadenas hoteleras de Cuba con datos recolectados en el 2005. [Abstract] From the use of the satisfaction index of the clients (Consumer Satisfaction Index) different methodologies has been developed for evaluating the work of hotels. The main interest is considering the attributes and services for establishing how they conform the client's satisfaction. Due to the nature of the problem, the population is dynamic; in fact, it is very usual that the recollection of the information is equivalent to a census. In many occasions, using samples allows completing the information. Therefore the usual statistical inference is not usable. Only descriptive statistical data analysis is of use and the modern tools may be used for deriving coherent analysis of the data. We consider the possibility that the manager will accept the validity of a certain super population model. Then is justified developing studies using methods as principal components for example. The discussion is illustrated with data collected in Cuban hotels in 2005

ACAPULCO’S TOURISM MARKET: TOURISTS PROFILE ANALYSIS The profile of the tourists visiting Acapulco is made. This study uses a sample of 399 tourists. The obtained results allow the identification of the satisfaction profile of the tourism in terms of the offers of the market