A class of PPS estimators variance using auxihary information.
A class of stopping rules for fixed precision sequential estimates
A class of tests for exponentiality based on a continuum of moment conditions
The empirical moment process is utilized to construct a family of tests for the null hypothesis that a random variable is exponentially distributed. The tests are consistent against the 'new better than used in expectation' (NBUE) class of alternatives. Consistency is shown and the limit null distribution of the test statistic is derived, while efficiency results are also provided. The finite-sample properties of the proposed procedure in comparison to more standard procedures are investigated via...
A class of unbiased kernel estimates of a probability density function
We propose a class of unbiased and strongly consistent nonparametric kernel estimates of a probability density function, based on a random choice of the sample size and the kernel function. The expected sample size can be arbitrarily small and mild conditions on the local behavior of the density function are imposed.
A classification of nonlinear regression models and parameter confidence regions
A collector for information without probability in a fuzzy setting
In the fuzzy setting, we define a collector of fuzzy information without probability, which allows us to consider the reliability of the observers. This problem is transformed in a system of functional equations. We give the general solution of that system for collectors which are compatible with composition law of the kind “inf”.
A combined Monte Carlo and quasi-Monte Carlo method with applications to option pricing.
A Comparative Analysis of the Dea-Ccr Model and the Vikor Method
A comparative study of microaggregation methods.
Microaggregation is a statistical disclosure control technique for microdata. Raw microdata (i.e. individual records) are grouped into small aggregates prior to publication. Each aggregate should contain at least k records to prevent disclosure of individual information. Fixed-size microaggregation consists of taking fixed-size microaggregates (size k). Data-oriented microaggregation (with variable group size) was introduced recently. Regardless of the group size, microaggregations on a multidimensional...
A comparative study of small area estimators.
It is known that direct-survey estimators of small area parameters, calculated with the data from the given small area, often present large mean squared errors because of small sample sizes in the small areas. Model-based estimators borrow strength from other related areas to avoid this problem. How small should domain sample sizes be to recommend the use of model-based estimators? How robust are small area estimators with respect to the rate sample size/number of domains?To give answers or recommendations...
A Comparison Between PPSWR and Chaudhuri's IPPS Procedures.
A comparison between two indices obtained by MDF.
A Comparison of Approximately Optimal Stratification given Proportional Allocation with other Methods of Stratification and Allocation.
A comparison of automatic histogram constructions
Even for a well-trained statistician the construction of a histogram for a given real-valued data set is a difficult problem. It is even more difficult to construct a fully automatic procedure which specifies the number and widths of the bins in a satisfactory manner for a wide range of data sets. In this paper we compare several histogram construction procedures by means of a simulation study. The study includes plug-in methods, cross-validation, penalized maximum likelihood and the taut string...
A comparison of cointegration tests
In this paper some of the cointegration tests applied to a single equation are compared. Many of the existent cointegration tests are simply extensions of the unit root tests applied to the residuals of the cointegrating regression and the habitual is no cointegration. However, some non residual-based tests and some tests of the opposite null hypothesis have recently appeared in literature. Monte Carlo simulations have been used for the power comparison of the nine selected tests (, , , ,...
A comparison of evidential networks and compositional models
Several counterparts of Bayesian networks based on different paradigms have been proposed in evidence theory. Nevertheless, none of them is completely satisfactory. In this paper we will present a new one, based on a recently introduced concept of conditional independence. We define a conditioning rule for variables, and the relationship between conditional independence and irrelevance is studied with the aim of constructing a Bayesian-network-like model. Then, through a simple example, we will...
A comparison of linearization and quadratization domains
In a nonlinear model, the linearization and quadratization domains are considered. In the case of a locally quadratic model, explicit expressions for these domains are given and the domains are compared.
A comparison of parametric models for mortality graduation. Application to mortality data for the Valencia Region (Spain).
The parametric graduation of mortality data has as its objective the satisfactory estimation of the death rates based on mortality data but using an age-dependent function whose parameters are adjusted from the crude rates obtainable directly from the data. This paper proposes a revision of the most commonly used parametric models and compares the result obtained with each of them when they are applied to the mortality data for the Valencia Region. As a result of the comparison, we conclude that...
A comparison of three optimality criteria for observation channels
A complete gradient clustering algorithm formed with kernel estimators
The aim of this paper is to provide a gradient clustering algorithm in its complete form, suitable for direct use without requiring a deeper statistical knowledge. The values of all parameters are effectively calculated using optimizing procedures. Moreover, an illustrative analysis of the meaning of particular parameters is shown, followed by the effects resulting from possible modifications with respect to their primarily assigned optimal values. The proposed algorithm does not demand strict assumptions...