Results 161 to 170 of about 315,233 (274)

Dynamic Spillovers Between FinTech, Blockchain, and Green Finance: A Quantile Connectedness Approach

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT This paper explores how financial innovation and environmental sustainability intersect by analyzing spillovers between FinTech, blockchain energy use, and green finance. Using a Quantile Vector Autoregression (QVAR) framework, we examine weekly data from 2018 to 2024 across 11 digital, environmental, and macro‐financial indices.
Mehmet Sahiner, Sisi Sung, James Devlin
wiley   +1 more source

Rethinking Climate Change on the Role of Human Power Generation, Alternative Perspectives, Potential Solutions, and a Plea for Action

open access: yesChemie Ingenieur Technik, EarlyView.
All energy matters Let us broaden the discussion on solutions to climate change. Greenhouse gases have upset the delicate equilibrium of the Earth's energy balance. Consequently, all sources of heat affect the temperature of the Earth. Although the amount of additional heat generated by humans is a fraction of that produced by the sun, it is generated ...
Martin Bertau   +2 more
wiley   +1 more source

Optimal model‐based design of experiments for parameter precision: Supercritical extraction case

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study investigates the process of chamomile oil extraction from flowers. A parameter‐distributed model consisting of a set of partial differential equations is used to describe the governing mass transfer phenomena in a cylindrical packed bed with solid chamomile particles under supercritical conditions using carbon dioxide as a solvent ...
Oliwer Sliczniuk, Pekka Oinas
wiley   +1 more source

Restricted Tweedie stochastic block models

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley   +1 more source

Rank‐based estimation of propensity score weights via subclassification

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang   +3 more
wiley   +1 more source

Predicting cervical cancer DNA methylation from genetic data using multivariate CMMP

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Epigenetic modifications link the environment to gene expression and play a crucial role in tumour development. DNA methylation, in particular, is gaining attention in cancer research, including cervical cancer, the focus of this study.
Hang Zhang   +5 more
wiley   +1 more source

On subset least squares estimation and prediction in vector autoregressive models with exogenous variables

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne   +2 more
wiley   +1 more source

Fluctuation theorems for autonomous work. [PDF]

open access: yesProc Natl Acad Sci U S A
Jarzynski C, Deffner S, Rahav S.
europepmc   +1 more source

Asymptotic properties of cross‐classified sampling designs

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley   +1 more source

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