Results 61 to 70 of about 2,165 (200)

Wavelet‐Based Hurst Exponent Estimation

WIREs Computational Statistics, Volume 18, Issue 3, September 2026.
The review explores how wavelet‐based methods for estimating the Hurst parameters have developed from their theoretical roots to real‐world applications in fields like biology, engineering, and telecommunications. The review aims to highlight key techniques, compare their strengths and limitations, and point out challenges that still need to be ...
Dixon Vimalajeewa, Fabrizio Ruggeri, Brani Vidakovic   +2 more
wiley   +1 more source

Reflecting about Selecting Noninformative Priors

, 2014
. Following the critical review of Seaman et al (2012)[17], we reflect on an essential aspect of Bayesian statistics, namely the selection of a prior density.
Christian P. Robert, Kamary, Kaniav, Kaniav Kamary, Robert, Christian P.   +3 more
core   +1 more source

Nonstationary Spatial Correlation of Earthquake Ground Motions in California

Earthquake Spectra, Volume 42, Issue 3, August 2026.
Assessing seismic risk to spatially distributed infrastructure systems requires realistic representations of spatially correlated ground motions. Existing models for the spatial correlations of ground motions rely on strong second‐order stationarity assumptions, under which the correlation structure is assumed to be invariant across space, potentially ...
Pengfei Wang, Busra Bocekli, Junhui Yang, Scott J. Brandenberg, Jonathan P. Stewart   +4 more
wiley   +1 more source

Bayesian Inference for Two-Parameter Gamma Distribution Assuming Different Noninformative Priors

Revista Colombiana de Estadística, 2013
In this paper distinct prior distributions are derived in a Bayesian inference of the two-parameters Gamma distribution. Noniformative priors, such as Jeffreys, reference, MDIP, Tibshirani and an innovative prior based on the copula approach are ...
FERNANDO ANTONIO MOALA, PEDRO LUIZ RAMOS, JORGE ALBERTO ACHCAR   +2 more
doaj  

Bayesian Analysis of the 3-Component Mixture of Exponential Distribution Assuming the Non-Informative Priors

Revista Colombiana de Estadística
Bayesian analysis of the 3-component mixture of an Exponential distribution under type-I right censoring scheme is considered in this paper. The Bayes estimators and posterior risks for the unknown parameters are derived under squared error loss function,
MUHAMMAD TAHIR, MUHAMMAD ASLAM
doaj   +1 more source

A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction

G3: Genes, Genomes, Genetics, 2017
There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is ...
Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, José Cricelio Montesinos-López, Francisco Javier Luna-Vázquez, Josafhat Salinas-Ruiz, José R. Herrera-Morales, Raymundo Buenrostro-Mariscal   +7 more
doaj   +1 more source

Quantifying Model Selection Uncertainty in Structural Analysis: Methodology and Application

Earthquake Engineering &Structural Dynamics, Volume 55, Issue 9, Page 1828-1844, 25 July 2026.
ABSTRACT With increasing focus on complex engineering systems under rare events, computational models are critical for predictions due to the scarcity or absence of data. However, selecting an appropriate model can be challenging. Using a single model without available test calibration could result in significant bias in performance predictions. A case
Ya‐Heng Yang, Tracy C. Becker
wiley   +1 more source

Beyond Fixed Thresholds: Optimizing Summaries of Wearable Device Data via Piecewise Linearization of Quantile Functions

Statistics in Medicine, Volume 45, Issue 15-17, July 2026.
ABSTRACT Wearable devices, such as actigraphy monitors and continuous glucose monitors (CGMs), capture high‐frequency data, which are often summarized by the percentages of time spent within fixed thresholds. For example, actigraphy data are categorized into sedentary, light, and moderate‐to‐vigorous activity, while CGM data are divided into ...
Junyoung Park, Neo Kok, Irina Gaynanova
wiley   +1 more source

On the uniqueness of probability matching priors

, 2007
Probability matching priors are priors for which Bayesian and frequentist inference, in the form of posterior quantiles, or confidence intervals, agree to some order of approximation.
Staicu, A-M, Reid, N, Reid, Nancy
core  

On the choice of a noninformative prior for Bayesian inference of discretized normal observations

Computational Statistics, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Elster, Clemens, Lira, Ignacio
openaire   +4 more sources