Results 61 to 70 of about 249 (156)
Asymptotics for selected Risk Measures under general assumptions
The first questions when reading the title could be: What is risk and how can we measure it, especially in practice? % and how (good) can we assess the risk in practice?
Zwingmann, Tobias +1 more
core +2 more sources
International audienceMany estimators of the extreme value index are functions of the $k_n$ largest observations of the sample and therefore can be seen as a functional of the $k_n$ upper tail quantile process.
Menneteau, Ludovic, Girard, Stéphane
core
Elastoplasticity Informed Kolmogorov–Arnold Networks Using Chebyshev Polynomials
ABSTRACT Multilayer perceptron (MLP) networks are predominantly used to develop data‐driven constitutive models for granular materials. They offer a compelling alternative to traditional physics‐based constitutive models in predicting non‐linear responses of these materials, for example, elastoplasticity, under various loading conditions. To attain the
Farinaz Mostajeran, Salah A. Faroughi
wiley +1 more source
Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices
Conditions are derived for the consistency of kernel estimators of the covariance matrix of a sum of vectors of dependent heterogeneous random variables, which match those of the currently best-known conditions for the central limit theorem, as required ...
Jong, R.M. de, Davidson, J.
core
Wasserstein Regression, Forecasting, and Change‐Point Detection for Daily Traffic Flow Distributions
ABSTRACT We develop a distribution‐valued framework for modeling, forecasting, and monitoring traffic flow counts by treating each day as a probability distribution summarized by jittered empirical quantile signatures. Inference is conducted under the 2‐Wasserstein geometry, which in one dimension is isometric to the L2(0,1)$$ {L}^2\left(0,1\right ...
Abdolnasser Sadeghkhani
wiley +1 more source
On functional central limit theorems for certain continuous time parameter stochastic processes
Weak invariance principles for certain continuous time parameter stochastic processes (including martingales and reverse martingales) are considered. Weak convergence in the sup-norm metric is also studied.continuous time-parameter functional central ...
Tsong, Y., Sen, P. K.
core
ABSTRACT The traditional model specification of stepped‐wedge cluster‐randomized trials assumes a homogeneous treatment effect across time while adjusting for fixed‐time effects. However, when treatment effects vary over time, the constant effect estimator may be biased.
Zhe Chen +6 more
wiley +1 more source
On the Foundational Arguments of Sufficient Dimension Reduction
Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley +1 more source
Fully Modified GLS Estimation for Seemingly Unrelated Cointegrating Polynomial Regressions
ABSTRACT A new feasible generalized least squares estimator is proposed. Our estimator incorporates (1) the inverse autocovariance matrix of multidimensional errors, and (2) second‐order bias corrections. The resulting estimator has the intuitive interpretation of applying a weighted least squares objective function to filtered data series.
Yicong Lin, Hanno Reuvers
wiley +1 more source
Cohomogeneity‐one solitons in Laplacian flow: Local, smoothly‐closing and steady solitons
Abstract We initiate a systematic study of cohomogeneity‐one solitons in Bryant's Laplacian flow of closed G2$\text{G}_2$‐structures on a 7‐manifold, motivated by the problem of understanding finite‐time singularities of that flow. Here, we focus on solitons with symmetry groups Sp(2)${\rm Sp}(2)$ and SU(3)${\rm SU}(3)$; in both cases, we prove the ...
Mark Haskins, Johannes Nordström
wiley +1 more source

