Results 11 to 20 of about 2,878 (136)
This study explores the origins of life by linking prebiotic chemistry, the emergence of information‐carrying molecules such as RNA and proteins, and philosophical questions about consciousness. The study emphasizes the role of molecular evolution in the Central Dogma and provides insights into the chemical origins of biology and the basis of life's ...
Harald Schwalbe +5 more
wiley +2 more sources
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
This study employed an adaptive iterative strategy combining machine learning algorithms, domain knowledge, experimental design, and experimental feedback to aim to precisely and quickly discover high‐entropy ceramics with excellent energy storage performance.
Haowen Liu +4 more
wiley +1 more source
Regional Adjustments to NGA‐West2 Ground‐Motion Models for Turkey
ABSTRACT This paper presents a ground‐motion model updating (GMMU) framework to adjust NGA‐West2 models for predicting a set of intensity measures in Turkey, including peak ground acceleration (PGA), peak ground velocity (PGV), and pseudo‐spectral acceleration (PSA) at periods ranging from 0.01 to 10 s. The GMMU framework integrates bias identification
Mao‐Xin Wang, Gang Wang
wiley +1 more source
Ensemble Kalman filter in latent space using a variational autoencoder pair
The use of the ensemble Kalman filter (EnKF) in strongly nonlinear or constrained atmospheric, oceanographic, or sea‐ice models can be challenging. Applying the EnKF in the latent space of a variational autoencoder (VAE) ensures that the ensemble members satisfy the balances and constraints present in the model.
Ivo Pasmans +4 more
wiley +1 more source
Data assimilation with extremum Monte Carlo methods
This study presents the extremum Monte Carlo filter as a data assimilation method and, in particular, a variant of the variational approach (three‐ and four‐dimensional variational), where the state estimates are obtained by solving an optimization problem numerically over a space of prediction functions, instead of the state space itself.
Karim Moussa, Siem Jan Koopman
wiley +1 more source
The importance of considering regimes in long‐term asset allocation to real estate
Abstract We investigate the long‐term, regime‐dependent asset allocation of an investor's wealth in a mixed‐asset portfolio that includes publicly traded real estate. We show that augmenting standard VAR models with Markov‐switching features not only improves predictive power for asset returns but also introduces economically meaningful horizon effects
Massimo Guidolin +2 more
wiley +1 more source
Abstract Generalizability theory (G‐theory) defines a statistical framework for assessing measurement reliability by decomposing observed variance into meaningful components attributable to persons, facets, and error. Classic G‐theory assumes homoscedastic residual variances across measurement conditions, an assumption that is often violated in ...
Philippe Rast, Peter E. Clayson
wiley +1 more source
A Comparative Review of Specification Tests for Diffusion Models
Summary Diffusion models play an essential role in modelling continuous‐time stochastic processes in the financial field. Therefore, several proposals have been developed in the last decades to test the specification of stochastic differential equations.
A. López‐Pérez +3 more
wiley +1 more source
On Integral Priors for Multiple Comparison in Bayesian Model Selection
Summary Noninformative priors constructed for estimation purposes are usually not appropriate for model selection and testing. The methodology of integral priors was developed to get prior distributions for Bayesian model selection when comparing two models, modifying initial improper reference priors. We propose a generalisation of this methodology to
Diego Salmerón +2 more
wiley +1 more source

