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To be able to resolve tomographic inversion problems in travel time, it is necessary the construction of distance matrices containing information of survey array geometry, the discretized domain shape and the distance traveled by rays in each area elements that compose it. Domain considered are generally rectangular for ease of geometric resolution. In this work is circular due to the need to carry out investigation in columns of this shape. Distance matrices are used to solve the linear system, which leads to the determination of velocity values in each element of the domain. Taking in mind discretization, there are several possibilities for the construction of arrays of pixels: may those be defined in one quadrant and obtaining the rest by symmetry; build arrays using any size pixels independent of the quadrant, and finally construct distance matrices with square pixels. Each option will provide access to new research possibilities. In this work an original procedure was developed for the construction of matrices with elements of the last type. The procedure was validated with simulated data using the damped least squares solution (DLSS) method, which demonstrated the efficiency of the algorithm. [ABSTRACT FROM AUTHOR]

In this work we have collected estimators of the population proportion through the use of auxiliary information under simple random sampling. We analyzed the main properties of these estimators. Theorethical properties suggest that the estimators with use of auxiliary information can outperform alternative methods, and the results derived from a Monte Carlo simulation study support this view. Has made an application on a population of Risk of Acidication in Lakes in the Northeastern states of the U.S. conducted by the Environmental Monitoring and Assessment Program of the US Environmental Protection Agency. In the application we have compared the different estimators each other with the standard stimators. [ABSTRACT FROM AUTHOR]

In the paper the results of the combined strategy formed by Robust Principal Component Analysis and CUR matrix decomposition are applied to a practical problem for adjusting a regression model by using Partial Least Squares (PLS). The conclusions concerning their advantages of such an approach as well information about the adjusted models are given. [ABSTRACT FROM AUTHOR]

The technique of Randomized Response has been introduced to reduce the risk of evasive answer or no-response in survey samplings of sensitive issues to estimate the total of individuals with that sensitive characteristic. We also know that highly efficient strategies of estimation require strong auxiliary information. Hence, in this article we obtain and compare two estimators: The Rao-Hartley-Cochran (RHC) estimator with Warner's model and the RHC estimator with Greenberg's model, both in a finite population setting. We will show via simulation that ŧA1,RHC,π the RHC π-estimator in Warner's model is less efficient than ŧA1,RHC,π, the RHC π-estimator in Greenberg's model. [ABSTRACT FROM AUTHOR]

In the first part of this paper the basics of the estimation of the stochastic production function is discussed. In the second part an application of the former is presented aimed at the hierarquization of the health institutions which depend of the Social Protection Ministry, according to a measure of the technical efficiency using inputs to maximise the output. For the present, a Cobb-Douglas production function is assumed with a symmetric noise and a semi-normal efficiency perturbation. Using maximum likelihood the parameters are obtained and the efficiency for each health institution is calculated. [ABSTRACT FROM AUTHOR]

There are models for estimation of the effort required in software projects that present limitations when they are used in early stages of the service life of development. In this article a revision of the existing models is presented and a new model able of estimating effort in the first stages of the development is described, whose entrances depend on both historical of projects made and on the experience of similar projects. The model exposed in this article was the result of an applied research project done between Universidad de Antioquia and Orbitel S.A., with the objective of considering the effort required by the analysts of the Management of Computer science for the creation and operation of solutions. Considering the historical available in Orbitel, our model gives precise estimations from the statistical point of view. Additionally, the proposed model can be simulated with a tool oriented to the Web. [ABSTRACT FROM AUTHOR]

This paper considers the problem of initial conditions that arise in estimating discrete stochastic process, and potentially useful solutions appear from a computational viewpoint. [ABSTRACT FROM AUTHOR]

Large-sample covariance matrices for the analysis of variance (ANOVA), minimum norm quadratic unbiased estimator (MINQUE), restricted maximum likelihood (REML), and maximum likelihood (ML) estimates of variance components are presented for the unbalanced one-way model when the underlying distributions are not necessarily normal. The limiting variances depend on the design sequence, on the actual values of the variance components, and on the kurtosis parameters of the underlying distributions. (The skewness parameters and other moments do not affect the limiting distributions.) Because all estimates are consistent and asymptotically normal, it is reasonable to compare the estimates using their asymptotic variances. Thus the efficiency of one estimate relative to another is defined as the ratio of their asymptotic variances, and these efficiencies are evaluated numerically and analytically for a variety of nonnormal situations. Various authors, including Hocking and Kutner (1975), Corbeil and Searle (1976), and Swallow and Monahan (1984), have compared the variances and/or mean squared errors of variance component estimates in a variety of finite-sample models assuming normally distributed effects. The purpose of this article is to extend this line of research to incorporate nonnormal distributions and large samples. Some special cases of MINQUE considered in this article are called MINQUE(0), MINOUE(1), MINOUE(Infinity), and MIVQUE (minimum variance quadratic unbiased estimator); these are defined by setting the a priori variance ratio to 0, 1, infinity (in a sense to be explained), and to the actual variance ratio, respectively. Because the actual variance ratio is usually unknown, the MIVQUE estimates cannot be computed for unbalanced designs. (In balanced designs MIVQUE and ANOVA correspond.) It turns out, however, that ML... [ABSTRACT FROM AUTHOR]

The usual ratio estimates for a population mean use information on an auxiliary variable to improve the estimation. The standard randomization analysis, however, does not take enough account of the observations on the auxiliary variable, so estimates and estimated variates can be conditionally biased unless the sample is balanced with respect to the auxiliary variable. I propose a method of adjustment for the bias of the estimate and its variance based only on the assumption of simple random sampling, which uses an approximate conditional distribution of the estimate given the mean of the auxiliary variable. Royall and Cumberland (1981) illustrated empirically that the usual random sampling estimates and estimated variances could be badly conditionally biased when samples were obtained that were unbalanced in the auxiliary variate. So if the sample mean and population mean, both of which are known at the time of analysis, are not close, it is known that the results are biased, but the usual random sampling formulas, which are purely unconditional, do not take account of this. They suggested that prediction models were necessary to adjust these. If the joint distribution of the sample means of the variate and covariate are considered together, then using the fact that these are asymptotically bivariate normal, it is possible to adjust approximately for the linear regression of the variate mean on the mean of the auxiliary variate. In this way a bias-adjusted estimate is suggested and formulas for the conditional variances of the estimates are obtained. A simulation study of two populations, one where the model on which the ratio estimate is based holds and one where it does not, is carried out to illustrate the improvements given by the results and to compare them with results based on the formulas... [ABSTRACT FROM AUTHOR]

The article is a technical comment on the negative correlation observed between the data-determined bandwidth and a value that minimizes ASE. This effect may also be demonstrated in a much simpler setting. This phenomenon is related to a negative correlation between ASE(h) and author's unbiased risk estimate, which was observed in a related situation. The negative correlation between unbiased estimates of bandwidths and their true values found here by author occurs widely and appears worthy of further study.