1,721,557 research outputs found
Multi split conformal prediction
No full textSplit conformal prediction is a computationally efficient method for performing distribution-free predictive inference in regression. It involves, however, a one-time random split of the data, and the result can strongly depend on the particular split. To address this problem, we propose multi split conformal prediction, a simple method based on Markov's inequality to aggregate split conformal prediction intervals across multiple splits
La questione sociale nel dissidio tra Valentiniano III ed Ezio
No full textSolari A. La questione sociale nel dissidio tra Valentiniano III ed Ezio. In: L'antiquité classique, Tome 2, fasc. 2, 1933. pp. 371-375
La versione ufficiale della morte di Valentiniano II
No full textSolari A. La versione ufficiale della morte di Valentiniano II. In: L'antiquité classique, Tome 1, fasc. 1-2, 1932. pp. 273-276
Minimally adaptive BH: A tiny but uniform improvement of the procedure of Benjamini and Hochberg
No full textWe define an adaptive procedure for control of the false discovery rate that is uniformly more powerful than the procedure of Benjamini and Hochberg. The power gain is tiny, however, and only appreciable for small numbers of hypotheses. We illustrate the new method with the case of two hypotheses, for which so far no procedure was known that controls false discovery rate but not also familywise error rate under positive dependence
Multiple hypothesis testing in genomics
No full textThis paper presents an overview of the current state of the art in multiple testing in genomics data from a user's perspective. We describe methods for familywise error control, false discovery rate control and false discovery proportion estimation and confidence, both conceptually and practically, and explain when to use which type of error rate. We elaborate on the assumptions underlying the methods and discuss pitfalls in the interpretation of results. In our discussion, we take into account the exploratory nature of genomics experiments, looking at selection of genes before or after testing, and at the role of validation experiments. © 2014 John Wiley & Sons, Ltd
The sequential rejection principle of familywise error control
No full textClosed testing and partitioning are recognized as fundamental principles of familywise error control. In this paper, we argue that sequential rejection can be considered equally fundamental as a general principle of multiple testing. We present a general sequentially rejective multiple testing procedure and show that many well-known familywise error controlling methods can be constructed as special cases of this procedure, among which are the procedures of Holm, Shaffer and Hochberg, parallel and serial gatekeeping procedures, modern procedures for multiple testing in graphs, resampling-based multiple testing procedures and even the closed testing and partitioning procedures themselves. We also give a general proof that sequentially rejective multiple testing procedures strongly control the familywise error if they fulfill simple criteria of monotonicity of the critical values and a limited form of weak familywise error control in each single step. The sequential rejection principle gives a novel theoretical perspective on many well-known multiple testing procedures, emphasizing the sequential aspect. Its main practical usefulness is for the development of multiple testing procedures for null hypotheses, possibly logically related that are structured in a graph. We illustrate this by presenting a uniform improvement of a recently published procedure. © Institute of Mathematical Statistics, 2010
Tecnologie solari a concentrazione: Produzione di calore a media temperatura
No full textTecnologie solari a concentrazione:Produzione di calore a media temperatura</div
PREDA: An R-package to identify regional variations in genomic data
No full textChromosomal patterns of genomic signals represent molecular ngerprints that may reveal how the local structural organization of a genome impacts the functional control mechanisms. Thus, the integrative analysis of multiple sources of genomic data and information deepens the resolution and enhances the interpretation of stand-alone high-throughput data. In this note, we present PREDA (Position RElated Data Analysis), an R package for detecting regional variations in genomics data. PREDA identies relevant chromosomal patterns in high-throughput data using a smoothing approach that accounts for distance and density variability of genomics features. Custom-designed data structures allow efciently managing diverse signals in different genomes. A variety of smoothing functions and statistics empower exible and robust workows. The modularity of package design allows an easy deployment of custom analytical pipelines. Tabular and graphical representations facilitate downstream biological interpretation of results. © The Author 2011. Published by Oxford University Press. All rights reserved
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