Results 91 to 100 of about 9,169 (255)

Advances in causal discovery methods for ecological time series

open access: yesBiological Reviews, EarlyView.
ABSTRACT Recent advances in data collection technologies (e.g. automated sensor networks, satellite remote sensing, and high‐throughput sequencing) have greatly expanded the availability of ecological time series, enabling new opportunities for causal analyses in dynamic ecosystems.
Kenta Suzuki   +6 more
wiley   +1 more source

Smoothed bootstrap and statistical data cloning for classifier evaluation

open access: yes, 2001
This paper is concerned with the estimation of a classifier’s accuracy. We present a number of novel bootstrap estimators, based on kernel smoothing, that consistently show superior performance on both synthetic and real data, with respect to other ...
Gregory Shakhnarovich
core  

Linking Corporate Ethics to Eco‐Innovation in SMES: The Mediating Role of Strategic Alliances and the Value Proposition

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT The ongoing deterioration of environmental quality and depletion of natural resources call for urgent corporate action towards sustainability. This study examines how corporate ethics influence eco‐innovation outcomes among small‐ and medium‐sized enterprises (SMEs) in the Spanish electronic components industry, considering the mediating roles
José Luis Ferreras‐Méndez   +1 more
wiley   +1 more source

Bias Corrected Bootstrap Bandwidth Selection [PDF]

open access: yes, 1996
Current bandwidth selectors for kernel density estimation that are asymptotically optimal often prove less promising under more moderate sample sizes.
Grund, Birgit   +3 more
core  

A Decision‐Making Model for Implementing Green Technology in Sustainable Building Projects

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT Green technology (GT) adoption is pivotal for reconciling environmental stewardship with economic viability in the built environment, particularly in resource‐constrained emerging economies. However, empirical evidence on how specific GT drivers actively mitigate adoption barriers remains scarce.
Abdelazim Ibrahim   +5 more
wiley   +1 more source

When Do Robots Go Green? Unveiling Mechanisms, Thresholds, and Spillovers of Industrial Robotics on Global Ecological Capacity

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT This paper examines the relationship between industrial robotics adoption and ecological capacity, measured by biocapacity, using panel data from 50 countries over the period 2000–2024. We investigate the transmission mechanisms, non‐linearities, spatial spillovers, and heterogeneity characterizing this relationship.
Brahim Bergougui   +1 more
wiley   +1 more source

Automating Sustainability: How Climate Action Unlocks the ESG Potential of Industrial Robotics

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT The convergence of Industry 4.0 and global sustainability goals presents a critical paradox: while automation drives efficiency, its net impact on comprehensive environmental, social, and governance (ESG) performance remains contested. This study investigates the relationship between industrial robot and country‐level ESG performance across 63
Brahim Bergougui
wiley   +1 more source

Finance 5.0, Digital Financial Inclusion, and Carbon Footprint: Evidence From a Multi‐Country Panel Using Threshold Models

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT This study investigates the impact of digital finance and financial inclusion on carbon emissions within a multi‐country panel framework, contributing to the emerging Finance 5.0 literature that links digital transformation with environmental sustainability.
Utku Altunöz
wiley   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos   +3 more
wiley   +1 more source

Bootstrap approximation of nearest neighbor regression function estimates

open access: yes, 1990
Let (X, Y) be a random vector in the plane and denote by m(x) = E(Y|X = x) the corresponding regression function. We show that the bootstrap approximation for the distribution of a smoothed nearest neighbor estimate of m(x) is valid.
Dikta, Gerhard
core   +1 more source

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