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A Tauberian Theorem for Weighted Means in Non-Archimedean Fields - Revisited and Revised

100%

Natarajan P. N.

Commentationes Mathematicae

2014

tom Vol 54, No. 2

177--178

In this note, K denotes a complete, non-trivially valued, non-archimedean field. We correct a Tauberian theorem for weighted means in K proved earlier in [1].

Finite Mixtures Model Approach to Sensitive Questions in Surveys

88%

Artem S. , Rostyslav M.

Statistics in Transition new series

2011

tom 12

nr 2

331-344

Observations from mixtures of different subpopulations are common in biological and sociological studies. We consider the case, when the observations are taken from a set of groups containing subjects, which belong to different subpopulations. Proportion of each subpopulation in a group is known and can vary from group to group. Our aim is to estimate the means of an observed variable for subjects, which belong to each subpopulation. In this paper we consider the case, when subpopulations are defined by answers on so called “sensitive questions”. We consider some parametric and nonparametric estimates of the subpopulation means, such as weighted means, maximum likelihood and weighted least squares estimates. Finite sample properties of these estimates are analyzed. Mean square errors of the estimates are compared on simulated data. Some asymptotic results are also given.

Supervised learning for record linkage through weighted means and OWA operators

75%

Torra V. , Navarro-Arribas G. , Abril D.

tom Vol. 39, no 4

1011-1026

Record linkage is a technique used to link records from one database with records from another database, making reference to the same individuals. Although it is normally used in database integration, it is also frequently applied in the context of data privacy. Distance-based record linkage permits linking records by their closeness. In this paper we propose a supervised approach for linking records with numerical attributes. We provide two different approaches, one based on the weighted mean and another on the OWA operator. The parameterization in both cases is determined as an optimization problem. We evaluate our proposal and compare it with standard distance based record linkage, which does not rely on the parameterization of the distance functions. To that end we test the proposal in the context of data privacy by linking a data file with its corresponding protected version.