1,372 research outputs found
Collective Outlier Detection and Enumeration with Conformalized Closed Testing
No full textThis paper develops a distribution-free method for collective outlier detection and enumeration, designed for situations in which the precise identification of individual outliers may be impractical due to the sparsity or weakness of their signals. This method builds upon the latest developments in conformal inference and blends them with more classical ideas from other areas, including multiple testing, rank tests, permutations, and non-parametric large-sample asymptotics. Key innovations include an extension of the Wilcoxon-Mann-Whitney test, which may be of some independent interest, and a principled algorithm for tuning the choices of machine learning classifier and two-sample testing procedure utilized by our method, yielding to an adaptive strategy. Assuming to have a control sample where all the observations are drawn independently from the same distribution (inlier distribution) and a test sample where possibly some observations are extracted from a different distribution (outlier distribution), our methodology implements the closed testing procedure providing simultaneous inference on the number of outliers in the test sample or in any subset of the test set. The inferential result produced by our method is a (1−α)-confidence lower bounds for the number of true outliers after any selection of the data in the test set. Further, we motivate theoretically the choice of the extended Wilcoxon-Mann-Whitney tests as local test in the closed testing procedure, studying their optimality and deriving interesting findings under distribution-free alternatives. Delving into how local optimality transfers to the closed testing procedure is prompt for future research. The effectiveness of our method is highlighted through extensive empirical demonstrations, including an analysis of the LHCO high-energy particle collision data set
Solari Aldo E. — Sociologia rural nacional
No full textG A. Solari Aldo E. — Sociologia rural nacional. In: Population, 13ᵉ année, n°4, 1958. p. 735
Contribution to the discussion of “A critical evaluation of the current ‘<i>p</i> -value controversy’”
No full textNo abstract is available for this article
Preface
No full textThis volume contains the Proceedings of the 13th Symposium on Conformal and Probabilistic Prediction with Applications (COPA2024), organised by Politecnico di Milano, Italy, and held in Milano on September 9-11, 2024. Overall, 2 keynotes speeches, 2 tutorials, 27 presentations and 5 posters have been presented during the conference. The rest of the publication includes full papers from the 27 presentations, one from one of the tutorials, and abstracts for the keynotes, one tutorial and the 5 posters
La desigualdad educativa: problemas y políticas
No full textIncluye BibliografíaEl presente número de la serie constituye un homenaje a Aldo Solari. Incluye, por un lado, notas biográficas y un análisis de la contribución de Solari a la sociología de la educación en América Latina. Por otro lado, reproduce el documento sobre la desigualdad educativa, problemas y políticas, publicado en 1988
Simultaneous directional inference
No full textWe consider the problem of inference on the signs of parameters. We aim
to provide post-hoc confidence bounds on the number of positive and
negative (or non-positive) parameters. The guarantee is simultaneous, for all
subsets of parameters. Our suggestion is as follows: start by using the data to
select the direction of the hypothesis test for each parameter; then, adjust
the -values of the one-sided hypotheses for the selection, and use the
adjusted -values for simultaneous inference on the selected one-sided
hypotheses. The adjustment is straightforward assuming that the -values of
one-sided hypotheses have densities with monotone likelihood ratio, and are
mutually independent. We show that the bounds we provide are tighter (often by
a great margin) than existing alternatives, and that they can be obtained by at
most a polynomial time. We demonstrate the usefulness of our simultaneous
post-hoc bounds in the evaluation of treatment effects across studies or
subgroups. Specifically, we provide a tight lower bound on the number of
studies which are beneficial, as well as on the number of studies which are
harmful (or non-beneficial), and in addition conclude on the effect direction
of individual studies, while guaranteeing that the probability of at least one
wrong inference is at most 0.05.Comment: 59 pages, 11 figures, 7 table
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