Results 31 to 40 of about 1,596,868 (270)
Analysis of influencing factors and prediction of China’s Containerized Freight Index
Frontiers in Marine Science, 2023 China, as a major maritime nation, the China Containerized Freight Index (CCFI) serves as an objective reflection of the Chinese shipping market and an important indicator for understanding China’s shipping industry globally.
Xiaoying Tu +3 more
doaj +1 more source
Model-robust regression and a Bayesian ``sandwich'' estimator [PDF]
, 2010 We present a new Bayesian approach to model-robust linear regression that leads to uncertainty estimates with the same robustness properties as the Huber--White sandwich estimator.
Lumley, Thomas +2 more
core +3 more sources
MENGATASI PENCILAN PADA PEMODELAN REGRESI LINEAR BERGANDA DENGAN METODE REGRESI ROBUST PENAKSIR LMS
Barekeng, 2019 Ordinary Least Squares (OLS) is frequent used method for estimating parameters. OLS estimator is not a robust regression procedure for the presence of outliers, so the estimate becomes inappropriate.
Farida Daniel
doaj +1 more source
Robust Surveillance Schemes Based on Proportional Hazard Model for Monitoring Reliability Data
Mathematics, 2023 Product reliability is a crucial component of the industrial production process. Several statistical process control techniques have been successfully employed in industrial manufacturing processes to observe changes in reliability-related quality ...
Moezza Nabeel +4 more
doaj +1 more source
Robust regression with imprecise data [PDF]
, 2011 We consider the problem of regression analysis with imprecise data. By imprecise data we mean imprecise observations of precise quantities in the form of sets of values.
Cattaneo, Marco E. G. V. +1 more
core +1 more source
Cellwise robust M regression [PDF]
Computational Statistics & Data Analysis, 2020 The cellwise robust M regression estimator is introduced as the first estimator of its kind that intrinsically yields both a map of cellwise outliers consistent with the linear model, and a vector of regression coefficients that is robust against vertical outliers and leverage points.
P. Filzmoser +4 more
openaire +3 more sources
Asymptotic equivalence and adaptive estimation for robust nonparametric regression [PDF]
, 2009 Asymptotic equivalence theory developed in the literature so far are only for bounded loss functions. This limits the potential applications of the theory because many commonly used loss functions in statistical inference are unbounded.
Cai, T. Tony, Zhou, Harrison H.
core +4 more sources
Robust Regression via Hard Thresholding [PDF]
, 2015 We study the problem of Robust Least Squares Regression (RLSR) where several response variables can be adversarially corrupted. More specifically, for a data matrix X \in R^{p x n} and an underlying model w*, the response vector is generated as y = X'w* +
Bhatia, Kush +2 more
core
Robust and Sparse Regression via $\gamma$-divergence
, 2016 In high-dimensional data, many sparse regression methods have been proposed. However, they may not be robust against outliers. Recently, the use of density power weight has been studied for robust parameter estimation and the corresponding divergences ...
Fujisawa, Hironori, Kawashima, Takayuki
core +1 more source
Cluster-Robust Bootstrap Inference in Quantile Regression Models [PDF]
, 2015 In this paper I develop a wild bootstrap procedure for cluster-robust inference in linear quantile regression models. I show that the bootstrap leads to asymptotically valid inference on the entire quantile regression process in a setting with a large ...
Hagemann, Andreas
core +4 more sources