Results 71 to 80 of about 4,889,303 (231)

Complex Versus Parsimonious Site‐Based Stochastic Ground Motion Models: Which One Is Better?

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Stochastic ground motion models (GMMs) provide a probabilistic representation of seismic input and are increasingly important for uncertainty quantification (UQ) in earthquake engineering. This study focuses on site‐based stochastic GMMs, which learn the statistical features of selected datasets of seismic records and generate statistically ...
Maijia Su, Mayssa Dabaghi, Marco Broccardo   +2 more
wiley   +1 more source

Prior elicitation in Bayesian quantile regression for longitudinal data [PDF]

, 2011
© 2011 Alhamzawi R, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original auhor and source are ...
Alhamzawi, Rahim, Rahim Alhamzawi, Pan, J, Yu, K, Yu, Keming, Pan, Jianxin, Al-Hamzawi, R, Keming Yu   +7 more
core   +1 more source

Surface-driven size scaling of the lattice parameter, Debye-Waller coefficient and microstrain in nanocrystals. [PDF]

Acta Crystallogr A Found Adv
This work develops three surface‐driven nanoscale models for the diffraction‐derived lattice parameter, Debye–Waller coefficient and microstrain, clarifying why their size dependences are not equally universal. Atomistic simulations and literature data show that lattice parameter trends depend strongly on capillarity, chemistry and defects, whereas the
Subbareddy S, Agnolin E, Malagutti MA, Ataollahi N, Dinnebier R, Scardi P.   +5 more
europepmc   +2 more sources

Loss‐Aware Forecast Construction for Realized Variance

Journal of Forecasting, EarlyView.
ABSTRACT Forecasts of realized variance are commonly constructed from models of log‐realized variance and then transformed back to the original scale. However, the resulting forecasts are often evaluated using loss functions defined in relative rather than absolute terms, creating a potential mismatch between forecast construction and forecast ...
Nick Taylor
wiley   +1 more source

Generalized Univariate Distributions and a New Asymmetric Laplace Model

, 2020
This work provides a survey of the general class of distributions generated from the mixture of the beta random variables. We provide an extensive review of the literature, concerning generating new distributions via the inverse CDF transformation. In particular, we accounted for beta generated and Kumaraswamy generated families of distributions.
openaire   +2 more sources

Asymmetric Power Distribution: Theory and Applications to Risk Measurement [PDF]

Theoretical literature in finance has shown that quantifying the risk of financial time series amounts to measuring their expected shortfall, also known as tail Value at Risk.
Ivana Komunjer
core  

Posterior Probabilities of Dominance for Wealth Distributions

Econometrics
Probability distributions, which are typically used to describe income distributions, are not suitable to describe a population’s distribution of wealth because of the existence of negative observations and a large concentration of values close to zero ...
William Griffiths, Duangkamon Chotikapanich   +1 more
doaj   +1 more source

Linear Mechatronic Modeling of Rectangular Tank Sloshing Dynamics

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Sloshing dynamics in partially filled tanks can strongly influence system‐level behavior when fluid motion couples with rigid‐body dynamics. This paper presents a linear and acausal two‐dimensional sloshing model for rectangular tanks, based on the reformulation of established sloshing theory within a modular, multi‐domain modeling framework ...
Magnus Steinstø, Eilif Pedersen
wiley   +1 more source

From Biological Fractal Dynamics to Analog Fractional‐Order Circuits: A System Design Framework Based on Operatorization Thought

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Fractional calculus, with its unique advantage in describing memory and nonlocal effects, has become a key tool for modeling nonlinear dynamic systems. Its integration with circuit systems has opened up a new paradigm for modern circuit design.
Zhimo Jian, Zheng Li, Gang Peng, Chaoqian Luo, Yajun Yin   +4 more
wiley   +1 more source

bayesQR: A Bayesian Approach to Quantile Regression

Journal of Statistical Software, 2017
After its introduction by Koenker and Basset (1978), quantile regression has become an important and popular tool to investigate the conditional response distribution in regression. The R package bayesQR contains a number of routines to estimate quantile
Dries F. Benoit, Dirk Van den Poel
doaj   +1 more source