Search results for "Probability"

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…

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…

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…

Probabilistic Logic under Coherence: Complexity and Algorithms

2005

In previous work [V. Biazzo, A. Gilio, T. Lukasiewicz and G. Sanfilippo, Probabilistic logic under coherence, model-theoretic probabilistic logic, and default reasoning in System P, Journal of Applied Non-Classical Logics 12(2) (2002) 189---213.], we have explored the relationship between probabilistic reasoning under coherence and model-theoretic probabilistic reasoning. In particular, we have shown that the notions of g-coherence and of g-coherent entailment in probabilistic reasoning under coherence can be expressed by combining notions in model-theoretic probabilistic reasoning with concepts from default reasoning. In this paper, we continue this line of research. Based on the above sem…

Modeling long-range memory with stationary Markovian processes

2009

In this paper we give explicit examples of power-law correlated stationary Markovian processes y(t) where the stationary pdf shows tails which are gaussian or exponential. These processes are obtained by simply performing a coordinate transformation of a specific power-law correlated additive process x(t), already known in the literature, whose pdf shows power-law tails 1/x^a. We give analytical and numerical evidence that although the new processes (i) are Markovian and (ii) have gaussian or exponential tails their autocorrelation function still shows a power-law decay =1/T^b where b grows with a with a law which is compatible with b=a/2-c, where c is a numerical constant. When a<2(1+c) th…

Supplementary material 13 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the …

2015

Individual assignments to genotypic clusters A, F1, F2, R1, R2: Explanation note: Posterior group membership probabilities (PGMPs) of male and female specimens as resulting from Discriminant Analysis of Principal Coordinates of wing landmarks (upper) or wing band areas (lower). Prior groups: A, F1, F2, R1, R2 (from white to dark blue).

Supplementary material 11 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the …

2015

Constrained ordination of wing band areas: Explanation note: Discriminant analysis of principal coordinates (DAPC) maximising morphometric differences in wing band areas between males and females (a) Ceratitis anonae, Ceratitis fasciventris and Ceratitis rosa and (b) genotypic clusters A, F1, F2, R1, R2.

Supplementary material 8 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the C…

2015

Unconstrained ordination of wing landmarks: Explanation note: Principal component analysis (PCA) showing morphometric differences in wing landmarks between males and females (a) Ceratitis anonae, Ceratitis fasciventris and Ceratitis rosa and (b) genotypic clusters A, F1, F2, R1, R2.

Supplementary material 4 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the C…

2015

Wing landmarks and wing band areas: Explanation note: Position of wing landmarks and wing band areas (numbers according to Suppl. material 3).