Results 51 to 60 of about 452,503 (268)

Volatility forecasting [PDF]

, 2005
Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical ...
Andersen, Torben G., Bollerslev, Tim, Christoffersen, Peter F., Diebold, Francis X.   +3 more
core   +6 more sources

Identifying gene expression signatures for risk stratification of postoperative adjuvant chemotherapy in colorectal cancer

FEBS Open Bio, EarlyView.
A novel signature integrating genome‐wide analysis with clinical factors predicts recurrence in stage II colorectal cancer and enables a new risk stratification to guide postoperative adjuvant chemotherapy. Clinical risk stratification for postoperative recurrence in patients with pathological stage II (pStage II) colorectal cancer (CRC) is essential ...
Mayuko Otomo, Keisuke Okuno, Shuichi Watanabe, Sakiko Oba, Hiroyasu Kagawa, Masanori Tokunaga, Daisuke Ban, Yusuke Kinugasa   +7 more
wiley   +1 more source

A Latent Variable Approach to Multivariate Quantitative Trait Loci [PDF]

, 2010
A novel approach based on latent variable modelling is presented for the analysis of multivariate quantitative and qualitative trait loci. The approach is general in the sense that it enables the joint analysis of many kinds of quantitative and ...
Bob O', Mikko J. Sillanpä, Outi Savolainen, Pä   +3 more
core   +1 more source

Hospital Readmission After Traumatic Brain Injury Hospitalization in Community‐Dwelling Older Adults

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the risk of hospital readmission after an index hospitalization for TBI in older adults. Methods Using data from the Atherosclerosis Risk in Communities (ARIC) study, we used propensity score matching of individuals with an index TBI‐related hospitalization to individuals with (1) non‐TBI hospitalizations (primary analysis)
Rachel Thomas, Connor A. Law, Joan A. Casey, Thomas Mosley, Rebecca F. Gottesman, Ramon Diaz‐Arrastia, Holly Elser, Andrea L. C. Schneider   +7 more
wiley   +1 more source

A Combined Framework Based on Feature Selection and Multivariate Mixed-Frequency for Crude Oil Prices Point and Interval Forecasting

IEEE Access, 2023
Effective crude oil price forecasting is essential for energy supply stabilization, investment decisions, policy formulation, and economic impact assessment.
Jun Long, Lue Li, Zejun Li
doaj   +1 more source

Fast and robust estimation of the multivariate errors in variables model

, 2003
In the multivariate errors in variable models one wishes to retrieve a linear relationship of the form y = ß x + a, where both x and y can be multivariate. The variables y and x are not directly measurable, but observed with measurement error. The classical approach to estimate the multivariate errors in variable model is based on an eigenvector ...
Croux, Christophe, Fekri, M., Ruiz-Gazen, A.   +2 more
openaire   +2 more sources

Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler, Vivian Maas, Arian Taheri Amin, Jennifer Faber, Tamara Schaprian, Katharina Hill, Matthis Synofzik, Lisa H. Graf, Heike Jacobi, Manuela Lima, Ana F. Ferreira, Bart P. van de Warrenburg, Ilse H. J. Willemse, Dagmar Timmann, Andreas Thieme, Paola Giunti, Hector Garcia‐Moreno, Magda M. Santana, Jeannette Hübener‐Schmid, Elin H. Davies, Thomas Klockgether   +20 more
wiley   +1 more source

Multivariate Covariance Generalized Linear Models

, 2015
We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models (McGLMs), designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation ...
Bonat, Wagner Hugo, Jørgensen, Bent
core   +1 more source

Vestibular Patient Journey: Insights From Vestibular Disorders Association (VeDA) Registry

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Vestibular symptoms impose a high burden of disability. Understanding real‐world diagnostic and treatment pathways can identify care gaps and guide interventions. We aimed to characterize symptom profiles, diagnostic trends, provider involvement, and treatment patterns in vestibular disorders.
Ali Rafati, Sami I. Nassar, Shaun A. Nguyen, Patricia L. Gerend, Michael C. Schubert, Michael T. Teixido, Frederick A. Godley, Joel A. Goebel, Cynthia A. Ryan, Habib G. Rizk, Amir Kheradmand   +10 more
wiley   +1 more source

Estimation in a Multivariate "Errors in Variables" Regression Model: Large Sample Results

The Annals of Statistics, 1981
In a multivariate "errors in variables" regression model, the unknown mean vectors $\mathbf{u}_{1i}: p \times 1, \mathbf{u}_{2i}: r \times 1$ of the vector observations $\mathbf{x}_{1i}, \mathbf{x}_{2i}$, rather than the observations themselves, are assumed to follow the linear relation: $\mathbf{u}_{2i} = \alpha + B\mathbf{u}_{1i}, i = 1,2,\cdots, n$.
openaire   +3 more sources