[PDF] Top 20 Conditional covariance estimation for dimension reduction and sensivity analysis

... thousands) for the evaluation of the model ...oceanography and others; the scientists have developed Monte-Carlo or quasi Monte-Carlo ...methods. For instance, the Fourier amplitude sensitivity test ... Voir le document complet

... inequalities and should be dealt with a more precise and care- ful asymptotic study on the effect of presmoothing borrowing for instance ideas from a recent work by Benko et ...Indeed, ... Voir le document complet

... Geodesic Analysis (PGA) Instead of an analysis of the covariance matrix, [13] proposed the minimization of squared distances to subspaces which are totally geodesic at a point, a procedure coined ... Voir le document complet

... ). For fixed dimen- sion, we also prove the asymptotic efficiency of this estimator, that performs asymptotically as well as as if the true block-diagonal structure were ...high dimension for ... Voir le document complet

... for learning features of expensive black-box functions ∗ Malek Ben Salem † , Fran¸ cois Bachoc ‡ , Olivier Roustant § , Fabrice Gamboa ‡ , and Lionel Tomaso ¶ ...sensitivity analysis is performed to ... Voir le document complet

... between covariance matrices is at the core of many machine learning and signal processing ...used for covariance features-based classification (for in- stance in brain signal or ... Voir le document complet

... Model and definition of the estimator 87 PCA regularization by expanding the empirical eigenvectors in a sparse basis and then apply a thresholding ...methodology for high-dimensional ... Voir le document complet

... 0, for |z| ≤ 1, (1.22) which is necessary and sufficient to guarantee that the stationary solution (X t ) only depends on «past» values {ε s : s ≤ t} of the ...) and, because of this, are regarded as ... Voir le document complet

... adjusted for covariates; ...simplistic for many real world ...covariates and the times that passes before some event occurs, including Faraggi-Simon network [4] who proposed a simple feed-forward as ... Voir le document complet

... Science and beyond. Proximity problems in metric spaces of low dimension have been typically handled by methods which discretize the space and therefore are affected by the curse of dimensionality, ... Voir le document complet

... 1], and the errors ε i are ...loss for different values of the sample size n for the first step estimator by SAMM, the final estimator provided by SAMM and the estimator based on ...of ... Voir le document complet

... Guyon and Vapnik, 1992 ; Vapnik, 1995 ), is due in part to relatively good performance on high dimensional problems, while the traditional kernel methods ...revived, and very promising research trend in ... Voir le document complet

... – r uw (neutral conditions): pronounced temporal dynamics – r wc and r wT (unstable conditions): no temporal dynamics. – r uw , r wc and r wT : pronounced spatial variability (r uw > r wT > r wc ). 𝑟 ... Voir le document complet

... Recently, covariance matrices have been modeled as realiza- tions of Riemannian Gaussian distributions (RGDs) and used in classification algorithms such as k-means or Expectation- Maximization (EM) ... Voir le document complet

... high), and these estimates are then extrapolated using the shape of the conditional heavy-tailed distribution to obtain estimators of properly extreme conditional ...assumptions, and the ... Voir le document complet

... the covariance matrix of an observation vector, using heterogeneous training samples, ...whose covariance matrices are not exactly ...same covariance matrix ...sample covariance matrix (SCM) ... Voir le document complet

... Intermediate expectiles estimation Y 1 , . . . , Y n are i.i.d. realizations of Y . If α n << 1 − 1/n (or equivalently n(1 − α n ) → ∞ as n → ∞) is an intermediate sequence, two approaches have been ... Voir le document complet

... a conditional assertion account, one needs to recognize that indicative conditionals are conveying information about the speaker’s epistemic ...a conditional assertion) from acceptance conditions ... Voir le document complet

... In this section we discuss modeling VaR and related Market Risk measures (MRMs) via conditional quantiles and other techniques.... In practical.[r] ... Voir le document complet

... quality and preference domains study the relation between con- sumers preference and the characteristics of products in order to find the must acceptable characteristics of these products by the consumers ... Voir le document complet