Search results for "Statistic"
showing 10 items of 12520 documents
A primer on statistically validated networks
2019
In this contribution we discuss some approaches of network analysis providing information about single links or single nodes with respect to a null hypothesis taking into account the heterogeneity of the system empirically observed. With this approach, a selection of nodes and links is feasible when the null hypothesis is statistically rejected. We focus our discussion on approaches using i) the so-called disparity filter and ii) statistically validated network in bipartite networks. For both methods we discuss the importance of using multiple hypothesis test correction. Specific applications of statistically validated networks are discussed. We also discuss how statistically validated netw…
A complex sampling design: a tourism case study
2009
Computable majorants of the limit load in Hencky’s plasticity problems
2018
Abstract We propose a new method for analyzing the limit (safe) load of elastoplastic media governed by the Hencky plasticity law and deduce fully computable bounds of this load. The main idea of the method is based on a combination of kinematic approach and new estimates of the distance to the set of divergence free fields. We show that two sided bounds of the limit load are sharp and the computational efficiency of the method is confirmed by numerical experiments.
Efficient checking of coherence and propagation of imprecise probability assessments
2000
We consider the computational difficulties in the checking of coherence and propagation of imprecise probability assessments. We examine the linear structure of the random gain in betting criterion and we propose a general methodology which exploits suitable subsets of the set of values of the random gain. In this way the checking of coherence and propagation amount to examining linear systems with a reduced number of unknowns. We also illustrate an example.
Applying fully tensorial ICA to fMRI data
2016
There are two aspects in functional magnetic resonance imaging (fMRI) data that make them awkward to analyse with traditional multivariate methods - high order and high dimension. The first of these refers to the tensorial nature of observations as array-valued elements instead of vectors. Although this can be circumvented by vectorizing the array, doing so simultaneously loses all the structural information in the original observations. The second aspect refers to the high dimensionality along each dimension making the concept of dimension reduction a valuable tool in the processing of fMRI data. Different methods of tensor dimension reduction are currently gaining popUlarity in literature…
Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study
2018
Background Recent discoveries in the fields of machine learning (ML), Ecological Momentary Assessment (EMA), computerized adaptive testing (CAT), digital phenotype, imaging, and biomarkers have brought about a new paradigm shift in medicine. Objective The aim of this study was to explore psychiatrists’ perspectives on this paradigm through the prism of new clinical decision support systems (CDSSs). Our primary objective was to assess the acceptability of these new technologies. Our secondary objective was to characterize the factors affecting their acceptability. Methods A sample of psychiatrists was recruited through a mailing list. Respondents completed a Web-based survey. A quantitative…
Development of Computerized Adaptive Testing for Emotion Regulation
2020
Emotion regulation (ER) plays a vital role in individuals’ well-being and successful functioning. In this study, we attempted to develop a computerized adaptive testing (CAT) to efficiently evaluate ER, namely the CAT-ER. The initial CAT-ER item bank comprised 154 items from six commonly used ER scales, which were completed by 887 participants recruited in China. We conducted unidimensionality testing, item response theory (IRT) model comparison and selection, and IRT item analysis including local independence, item fit, differential item functioning, and item discrimination. Sixty-three items with good psychometric properties were retained in the final CAT-ER. Then, two CAT simulation stud…
Turismo e comunicazione tra mobilità fisiche e virtuali (e-book)
2012
From imprecise probability assessments to conditional probabilities with quasi additive classes of conditioning events
2012
In this paper, starting from a generalized coherent (i.e. avoiding uniform loss) intervalvalued probability assessment on a finite family of conditional events, we construct conditional probabilities with quasi additive classes of conditioning events which are consistent with the given initial assessment. Quasi additivity assures coherence for the obtained conditional probabilities. In order to reach our goal we define a finite sequence of conditional probabilities by exploiting some theoretical results on g-coherence. In particular, we use solutions of a finite sequence of linear systems.
Imprecise probability assessments and the Square of Opposition
There is a long history of investigations on the square of opposition spanning over two millenia. A square of opposition represents logical relations among basic sentence types in a diagrammatic way. The basic sentence types, traditionally denoted by A (universal affirmative: ''Every S is P''), E (universal negative: ''No S is P''), I (particular affirmative: ''Some S are P''), and O (particular negative: ''Some S are not P''), constitute the corners of the square, and the logical relations--contradiction, contrarity, subalternation, and sub-contrarity--form the diagonals and the sides of the square. We investigate the square of opposition from a probabilistic point of view. To manage impre…