Results 81 to 90 of about 389,136 (225)

On the symmetrized s-divergence

Open Mathematics, 2020
In this study, we work with the relative divergence of type s,s∈ℝs,s\in {\mathbb{R}}, which includes the Kullback-Leibler divergence and the Hellinger and χ 2 distances as particular cases.
Simić Slavko, Alzaid Sara Salem, Aydi Hassen   +2 more
doaj   +1 more source

Inverse sky islands: lowland river valleys drive microbial divergence while high elevations select for convergence in massive mountain ecosystems

Ecography, EarlyView.
Mountain ecosystems are often interpreted through the lens of the ‘sky island' model, where high‐elevation habitats function as isolated archipelagos. However, this model's applicability to massive, topographically complex mountain ranges where highlands are continuous and lowlands are fragmented remains untested.
Yazhou Zhang, J. Aaron Hogan, Jianjun Wang, Wenguang Sun, Yaojun Ye, Xin Liu, Minshu Song, Hang Sun   +7 more
wiley   +1 more source

The McMillan Theorem for Colored Branching Processes and Dimensions of Random Fractals

Entropy, 2014
For the simplest colored branching process, we prove an analog to the McMillan theorem and calculate the Hausdorff dimensions of random fractals defined in terms of the limit behavior of empirical measures generated by finite genetic lines.
Victor Bakhtin
doaj   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Lost in Translation? Risk‐Adjusting RMSE for Economic Forecast Performance

Journal of Forecasting, EarlyView.
ABSTRACT When used for parameter optimization and/or model selection, traditional mean squared error (MSE)–based measures of forecast accuracy often exhibit a weak or even negative correlation with the economic value of return forecasts measured by, for example, the Sharpe ratios of the resulting portfolios.
Lukas Salcher, Sebastian Stöckl, Michael Hanke   +2 more
wiley   +1 more source

Fendioxypyracil, a new and systemic PPO‐inhibiting herbicide for X‐spectrum weed control

Pest Management Science, EarlyView.
This graphical abstract presents the discovery and synthesis of PPO herbicide structures with a central pyridine core, showing molecular conformations, dose–response inhibition curves for PPO1 and PPO2, and comparative weed and grass control efficacy of fendioxypyracil versus other herbicides in greenhouse and field trials.
Tobias Seiser, Aimone Porri, Philipp Johnen, Silke Zeyer, Judith Wahrheit, Michael Betz, Breght Vandenberghe, Scott Asher, Liliana Parra Rapado   +8 more
wiley   +1 more source

Efficient ECG classification based on the probabilistic Kullback-Leibler divergence

Informatics in Medicine Unlocked
Diagnostic systems of cardiac arrhythmias face early and accurate detection challenges due to the overlap of electrocardiogram (ECG) patterns. Additionally, these systems must manage a huge number of features.
Dhiah Al-Shammary, Mohammed Radhi, Ali Hakem AlSaeedi, Ahmed M. Mahdi, Ayman Ibaida, Khandakar Ahmed   +5 more
doaj   +1 more source

On Weighted Kullback–Leibler Divergence for Doubly Truncated Random Variables

Revstat Statistical Journal, 2019
In this communication, we study doubly truncated weighted Kullback–Leibler divergence (KLD) between two nonnegative random variables. The proposed measure is a generalization of the dynamic weighted KLD introduced by Yasaei Sekeh et al. (2013).
Rajesh Moharana , Suchandan Kayal
doaj   +1 more source

A structurally localized ensemble Kalman filtering approach

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We derive an inherently localized ensemble Kalman filtering (EnKF) approach, avoiding the need for any auxiliary localization technique. The idea is to first use the variational Bayesian optimization to approximate the (continuous) state analysis probability density function (pdf) by a product of independent marginal pdfs corresponding to small ...
Boujemaa Ait‐El‐Fquih, Ibrahim Hoteit   +1 more
wiley   +1 more source

Online monitoring scheme using principal component analysis through Kullback-Leibler divergence analysis technique for fault detection

Transactions of the Institute of Measurement and Control, 2019
Principal component analysis (PCA) is a common tool in the literature and widely used for process monitoring and fault detection. Traditional PCA is associated with the two well-known control charts, the Hotelling’s T2 and the squared prediction error ...
Wahiba Bounoua, Amina B Benkara, A. Kouadri, Azzeddine Bakdi   +3 more
semanticscholar   +1 more source