A visual display device for significant features in complicated signals

DOI10.1016/j.csda.2004.01.010zbMath1429.62432OpenAlexW2016965451MaRDI QIDQ957113

Tor Arne Øigård, Fred Godtliebsen

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2004.01.010

zbMATH Keywords

regressionblurringsizerposterior smoothingsignificant features

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Density estimation (62G07)

Related Items (13)

Statistical inference and visualization in scale-space using local likelihood ⋮ SiZer Inference for Varying Coefficient Models ⋮ Nonparametric estimation of a log-variance function in scale-space ⋮ Statistical Scale Space Methods ⋮ Theoretical investigation of an exploratory approach for log-density in scale-space ⋮ Bayesian multiscale analysis of images modeled as Gaussian Markov random fields ⋮ An exploratory data analysis in scale-space for interval-valued data ⋮ Bayesian analysis of features in a scatter plot with dependent observations and errors in predictors ⋮ SiZer analysis for the comparison of time series ⋮ Scale space multiresolution analysis of random signals ⋮ Bayesian multiscale analysis for time series data ⋮ Statistical inference and visualization in scale-space for spatially dependent images ⋮ Nonparametric estimation of single-index models in scale-space

Uses Software

• fda (R)
• SiZer

Cites Work

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• Fast Sampling of Gaussian Markov Random Fields
• Functional data analysis
• Multiscale testing of qualitative hypotheses
• An Effective Bandwidth Selector for Local Least Squares Regression
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Design-adaptive Nonparametric Regression
• Edge-Preserving Smoothers for Image Processing
• Adaptive Markov Chain Monte Carlo through Regeneration
• SiZer for Exploration of Structures in Curves
• Equation of State Calculations by Fast Computing Machines
• SiZer for jump detection
• Monte Carlo sampling methods using Markov chains and their applications

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