Results 61 to 70 of about 131,402 (244)

Forecasting New Employment Using Nonrepresentative Online Job Advertisements With an Application to the Italian and EU Labor Market

Journal of Forecasting, EarlyView.
ABSTRACT Using online job advertisement data improves the timeliness and granularity depth of analysis in the labor market in domains not covered by official data. Specifically, its variation over time may be used as an anticipator of official employment variations.
Pietro Giorgio Lovaglio, Mario Mezzanzanica   +1 more
wiley   +1 more source

Universal efficiency at optimal work with Bayesian statistics

, 2010
If the work per cycle of a quantum heat engine is averaged over an appropriate prior distribution for an external parameter $a$, the work becomes optimal at Curzon-Ahlborn efficiency.
E. T. Jaynes, H. Jeffreys, H. Jeffreys, H. S. Leff, J. Gemmer, Ramandeep S. Johal   +5 more
core   +1 more source

Creation of a Landslide Susceptibility Map Using Short‐Term Data From the July 2018 Heavy Rainfall in Southern Hiroshima Prefecture

Geological Journal, EarlyView.
This work advances landslide susceptibility mapping by incorporating short‐term trigger data with landscape susceptibility mapping. We also examine the importance of downsampling, watershed delineation and geospatial correlations in evaluating outcomes.
Kanta Kotsugi, Ting Liu, Toshiro Hata, Rebecca Muenich   +3 more
wiley   +1 more source

Coevolutionary Algorithm with Bayes Theorem for Constrained Multiobjective Optimization

Mathematics
The effective resolution of constrained multi-objective optimization problems (CMOPs) requires a delicate balance between maximizing objectives and satisfying constraints.
Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi   +3 more
doaj   +1 more source

Posterior probability and fluctuation theorem in stochastic processes

, 2009
A generalization of fluctuation theorems in stochastic processes is proposed. The new theorem is written in terms of posterior probabilities, which are introduced via the Bayes theorem.
Crooks G. E., Crooks G. E., Crooks G. E., Dorosz S., Gallavotti G., Gallavotti G., Gaspard P., Harris R. J., Hatano T., Jarzynski C., Jarzynski C., Komatsu T. S., Komatsu T. S., Komatsu T. S., Kurchan J., Lebowitz J. L., Maes C., Maragakis P., Nishimori H., Oono Y., Seifert U., Seifert U.   +21 more
core   +1 more source

Robust Tests of Forecast Accuracy for Factor‐Augmented Regressions With an Application to the Novel EA‐MD‐QD Dataset

Journal of Applied Econometrics, EarlyView.
ABSTRACT We present four novel tests of equal predictive accuracy and encompassing á Pitarakis (2023, 2025) for factor‐augmented regressions. Factors are estimated using cross‐section averages (CAs) of grouped series and our theoretical findings are empirically relevant: asymptotic normality, robustness to an overspecification of the number of factors,
Alessandro Morico, Ovidijus Stauskas
wiley   +1 more source

Extending the hyper‐logistic model to the random setting: New theoretical results with real‐world applications

Mathematical Methods in the Applied Sciences, EarlyView.
We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés, Ana Navarro‐Quiles, Sorina Madalina Sferle   +2 more
wiley   +1 more source

Interpretation of Evidence: The Key to Conveying Information to Court

Arab Journal of Forensic Sciences & Forensic Medicine, 2019
The advent of new technologies such as DNA typing, the weight of scientific evidence in criminal trials of widespread publicity, and the proliferation of fictional and non-fictional works in popular media have contributed to making forensic science well ...
Marta Da Pian, Pietro Carresi, Valerio Causin   +2 more
doaj   +1 more source

An objective Bayesian method for including parameter uncertainty in ensemble model output statistics

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Conventional model output statistics and ensemble model output statistics methods for calibrating ensemble forecasts lead to severe underestimation of the probabilities of ensemble extremes (in blue). This is because they ignore statistical parameter uncertainty.
Stephen Jewson, Leonardo Olivetti, Gabriele Messori, Paul J. Northrop, Trevor Sweeting   +4 more
wiley   +1 more source

Classifying with the Fine Structure of Distributions: Leveraging Distributional Information for Robust and Plausible Naïve Bayes

Machine Learning and Knowledge Extraction
In machine learning, the Bayes classifier represents the theoretical optimum for minimizing classification errors. Since estimating high-dimensional probability densities is impractical, simplified approximations such as naïve Bayes and k-nearest ...
Quirin Stier, Jörg Hoffmann, Michael C. Thrun   +2 more
doaj   +1 more source