Detection and handling outliers in longitudinal data: wavelets decomposition as a solution

DOI10.1080/03610918.2022.2050389MaRDI QIDQ6558517

Unnamed Author, Berna Yazici, Ahmet Dundar Sezer

Publication date: 19 June 2024

Published in: Communications in Statistics. Simulation and Computation (Search for Journal in Brave)

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonparametric regression analysis of longitudinal data
• Detection of outliers in longitudinal count data via overdispersion
• Outliers and the ostensibly heavy tails
• Wavelet improvement in turning point detection using a hidden Markov model: from the aspects of cyclical identification and outlier correction
• Wavelet-based detection of outliers in financial time series
• Backfitting and local likelihood methods for nonparametric mixed-effects models with longitudinal data
• Performance of Some Resistant Rules for Outlier Labeling
• THE MULTIFRACTAL FORMALISM REVISITED WITH WAVELETS
• Incremental Refinement of Computation for the Discrete Wavelet Transform
• IPO estimation of heaviness of the distribution beyond regularly varying tails
• WAVELET TRANSFORM ASYMMETRIC WINSORIZED MEAN IN DETECTING OUTLIER VALUES
• A Bayesian approach to some outlier problems
• Successive refinement of information
• Longitudinal Data Analysis
• Wavelet methods in (financial) time-series processing

This page was built for publication: Detection and handling outliers in longitudinal data: wavelets decomposition as a solution