Results 181 to 190 of about 166,499 (273)

Single pointwise samples of electric field on a neuron model cannot predict activation threshold by brain stimulation. [PDF]

Brain Stimul
Wang B, Hussain MA, Worbs T, Thielscher A, Grill WM, Peterchev AV.   +5 more
europepmc   +1 more source

Navigating Supply Shocks: Sector Resilience and Production Prices Through Stochastic Input–Output Modeling

Mathematical Finance, EarlyView.
ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici, Gianluca Fusai, Anna Maria Gambaro, Daniele Marazzina   +3 more
wiley   +1 more source

Heteroskedastic Structural Vector Autoregressions Identified via Long‐Run Restrictions

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT A central assumption for identifying structural shocks in vector autoregressive (VAR) models via heteroskedasticity is the time‐invariance of the impact effects of the shocks. It is shown how that assumption can be tested when long‐run restrictions based on the cointegration structure of the variables are available for identifying structural ...
Martin Bruns, Helmut Lütkepohl
wiley   +1 more source

Evaluation of the visual field test algorithm: the Ambient Interactive ZEST-EX (AIZE-EX). [PDF]

Sci Rep
Nomoto H, Matsumoto C, Yoshikawa K, Nanno M, Kimura S, Inoue S, Yamanaka K, Kusaka S.   +7 more
europepmc   +1 more source

Confidence Intervals for Price Discovery

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT This paper discusses asymptotic and bootstrap confidence intervals for multivariate permanent‐transitory decompositions of cointegrated vector autoregressive I(1) systems, with a focus on price discovery. Alternative estimators of the permanent components are compared in terms of efficiency also under separable linear restrictions on the ...
Heino Bohn Nielsen, Paolo Paruolo, Anders Rahbek   +2 more
wiley   +1 more source

The Impact of Myopia on Regional Visual Field Loss and Progression in Glaucoma. [PDF]

Transl Vis Sci Technol
Lokhande A, Song L, Pang Y, Luo Y, Pasquale LR, Wellik SR, De Moraes CG, Myers JS, Eslami M, Elze T, Shen LQ, Zebardast N, Friedman DS, Boland MV, Wang M.   +14 more
europepmc   +1 more source

Least Trimmed Squares: Cointegration and Outliers

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT When applying the cointegrated autoregressive distributed lag model it is common to include indicator variables for outliers. This is often done in a somewhat ad hoc way. Least Trimmed Squares estimation provides a more systematic approach. This estimator is robust to a large number of outliers of many types.
Vanessa Berenguer‐Rico, Bent Nielsen
wiley   +1 more source

Three‐dimensional digital quantitative analysis of periodontal and peri‐implant phenotype—A narrative review

Periodontology 2000, EarlyView.
Abstract 3D digital evaluation of the periodontal and peri‐implant tissue, including CBCT, intraoral scanning, optical surface scanning, and ultrasonography, is being used in the clinical arena with increasing frequency. Thus, to validate the utilization of 3D digital analysis for this purpose, a critical evaluation of the reliability of digital ...
Yi Te Lin, Chenshuang Li, Jonathan Korostoff, Joseph P. Fiorellini, Jie Yang, Yu‐Cheng Chang   +5 more
wiley   +1 more source

Interpretable longitudinal glaucoma visual field estimation deep learning system from fundus images and clinical narratives. [PDF]

NPJ Digit Med
Huang X, Kong X, Yan Y, Gao Z, Li Z, Zhang C, Jin K, Ye J.   +7 more
europepmc   +1 more source

Spatial depth for data in metric spaces

Scandinavian Journal of Statistics, EarlyView.
Abstract We propose a novel measure of statistical depth, the metric spatial depth, for data residing in an arbitrary metric space. The measure assigns high (low) values for points located near (far away from) the bulk of the data distribution, allowing quantifying their centrality/outlyingness.
Joni Virta
wiley   +1 more source