Results 71 to 80 of about 566,338 (299)
We consider the problem of the estimation of the mean squared error (MSE) of some domain mean predictor for Fay‑Herriot model. In the simulation study we analyze properties of eight MSE estimators including estimators based on the jackknife method (Jiang,
Małgorzata Karolina Krzciuk
doaj +1 more source
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
This study aims to model large third-party liability insurance claim data using an exponential mixture distribution with a parametric bootstrap approach.
Ainani Tajriyan Muntaharridwan +1 more
doaj +1 more source
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong +7 more
wiley +1 more source
Introducing model uncertainty in time series bootstrap [PDF]
It is common in parametric bootstrap to select the model from the data, and then treat it as it were the true model. Kilian (1998) have shown that ignoring the model uncertainty may seriously undermine the coverage accuracy of bootstrap confidence ...
Peña, Daniel +2 more
core +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Asymptotic refinements of bootstrap tests in a linear regression model ; A CHM bootstrap using the first four moments of the residuals [PDF]
We consider linear regression models and we suppose that disturbances are either Gaussian or non Gaussian. Then, by using Edgeworth expansions, we compute the exact errors in the rejection probability (ERPs) for all one-restriction tests (asymptotic and ...
Pierre-Eric Treyens
core
This study uncovers an unusual RNAi pathway in the rhizarian pathogen Plasmodiophora brassicae. In the absence of Dicer, a Drosha‐like RNase III protein supports the biogenesis of predominant 21‐nt small RNAs, and two Argonaute proteins mediate small RNA‐guided silencing.
Xiong Zhang +13 more
wiley +1 more source
A new approach to bootstrap inference in functional coefficient models [PDF]
We introduce a new, factor based bootstrap approach which is robust under heteroskedastic error terms for inference in functional coefficient models. Modeling the functional coefficient parametrically, the bootstrap approximation of an F statistic is ...
Herwartz, Helmut, Xu, Fang
core
This study proposes parametric bootstrap estimation methods to improve features of the non-parametric bootstrap estimator of Incidence of Inefficiency proposed in the literature. This study is the first to propose parametric bootstrap estimation methods to improve features of the IOI estimators.
Deniz Özonur, Mehmet Güray Ünsal
openaire +1 more source

