Results 31 to 40 of about 4,586 (136)

Digital Technologies Disclosure and the Cost of Capital: The Mediating Role of Sustainability Performance

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines the economic consequences of Digital Technologies Disclosure (DTD), focusing on its impact on the cost of capital. The increasing significance of digital transformation in shaping corporate strategies and market perceptions motivates the study.
Hussein Mohsen Saber Ahmed, Awad Elsayed Awad Ibrahim, Khaldoon Albitar   +2 more
wiley   +1 more source

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer, Kristofer Månsson, Pär Sjölander, Gazi Salah Uddin   +3 more
wiley   +1 more source

Random Integrated Subdata Ensemble Method for Key Variable Selection in Rare Event Setting

Journal of Forecasting, EarlyView.
ABSTRACT We propose a general variable selection procedure to identify key input variables by applying elastic net regression to representative subdata in place of the full sample to select variables. We combine the lists of selected variables from each subdata through ensemble techniques, using the frequency of selecting the variable across different ...
Ching‐Chi Yang, Justin Deng, Lih‐Yuan Deng, Henry Horng‐Shing Lu   +3 more
wiley   +1 more source

Forecasting House Prices: The Role of Market Interconnectedness

Journal of Forecasting, EarlyView.
ABSTRACT While the existing research uncovers interconnections between various housing markets, it largely ignores the question of whether such linkages can improve house price predictions. To address this issue, we proceed in two steps. First, we forecast disaggregated house price growth rates from Australia and China to determine whether ...
Zac Chen, George Milunovich, Shuping Shi, Ben Wang   +3 more
wiley   +1 more source

Decoding temporal miRNA signatures of semen under in vitro exposure for forensic time since deposition estimation using machine learning‐driven modeling

Interdisciplinary Medicine, EarlyView.
This study develops a novel miRNA‐based framework for estimating the time since deposition of semen stains, combining small RNA sequencing with machine learning. Time‐dependent miRNA modules were identified using Mfuzz clustering and WGCNA, followed by a multi‐stage feature selection pipeline that reduced 261 candidate miRNAs to a minimal 7‐miRNA panel.
Meiming Cai, Qiong Lan, Tong Xie, Qinglin Liu, Ming Zhao, Xiaolian Wu, Xin Shi, Ruonan Shen, Yiman Wu, Chen Mao, Bin Cong, Bofeng Zhu   +11 more
wiley   +1 more source

Lecture notes on ridge regression

, 2020
The linear regression model cannot be fitted to high-dimensional data, as the high-dimensionality brings about empirical non-identifiability. Penalized regression overcomes this non-identifiability by augmentation of the loss function by a penalty (i.e ...
van Wieringen, Wessel N.
core  

Single‐Cell Transcriptomic Analysis Reveals Epithelial‐Mesenchymal Transition and Key Gene AGRN as a Universal Programme in Gastrointestinal Tumours by an Artificial Intelligence‐Derived Prognostic Index

Med Research, EarlyView.
Intra‐tumour heterogeneity is present in gastrointestinal tumours at the single‐cell level. Cell cycling, EMT, MYC and TNF‐α are the four main consensus meta‐programs in gastrointestinal tumours. Then, a prognostic model based on intratumoral heterogeneity was constructed using an artificial intelligence‐derived prognostic index.
Zhizhan Ni, Pengyuan Zhu, Liming Liu, Haiyang Wang, Jinzhe Zhou, Xianqing Wang, Song Wang, Liangchen Zhu, Songze Zhang, Yongxin Zhou, Bujun Ge, Qi Huang, Chenshen Huang   +12 more
wiley   +1 more source

Ridge Estimation of Inverse Covariance Matrices from High-Dimensional Data

, 2015
We study ridge estimation of the precision matrix in the high-dimensional setting where the number of variables is large relative to the sample size. We first review two archetypal ridge estimators and note that their utilized penalties do not coincide ...
Peeters, Carel F. W., van Wieringen, Wessel N.   +1 more
core   +2 more sources

Development and Validation of a Nomogram for Predicting Urinary Tract Infection After Urodynamic Study

Neurourology and Urodynamics, EarlyView.
ABSTRACT Introduction The use of antibiotic prophylaxis before urodynamic studies has been debated for a long time, with no clear consensus among international guidelines. Based on identified predictors of urinary tract infection after urodynamic studies, this study aims to develop and internally validate a nomogram to predict post‐urodynamic study ...
Omri Schwarztuch Gildor, Elad Yosef, Netanel Levin, Anna Itshak, Rony Vainrib, Amos Neheman, Michael Vainrib   +6 more
wiley   +1 more source

Opening the Black Box of Nonprofit Reputation and Volunteer Attraction With Supervised Machine Learning

Nonprofit Management and Leadership, EarlyView.
ABSTRACT With the aim to explore the potential of machine learning for nonprofit research, this article contrasts traditional linear regression with four contemporary supervised machine learning approaches. Concretely, we predict (1) reputation ratings and (2) the total number of volunteers for 4021 non‐profit organizations in the U.S.
Moritz Schmid, Hannes Lampe, Jurgen Willems   +2 more
wiley   +1 more source