Robust estimation of linear state space models

DOI10.1080/03610918.2017.1422752OpenAlexW2756661924MaRDI QIDQ5085964

Ruben Crevits, Christophe Croux

Publication date: 30 June 2022

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

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/617856

zbMATH Keywords

outliersKalman filterforecastingtime varying parameters

Mathematics Subject Classification ID

Robustness and adaptive procedures (parametric inference) (62F35) Discrete-time Markov processes on general state spaces (60J05)

Uses Software

• itsmr

Cites Work

• Unnamed Item
• Unnamed Item
• Robust Kalman tracking and smoothing with propagating and non-propagating outliers
• Robust estimation for ARMA models
• Kalman filter with outliers and missing observations
• Adaptively robust filtering for kinematic geodetic positioning.
• Influence function and efficiency of the minimum covariance determinant scatter matrix estimator
• The maximum likelihood least squares based iterative estimation algorithm for bilinear systems with autoregressive moving average noise
• Robust bayesian estimation for the linear model and robustifying the Kalman filter
• Introduction to Time Series and Forecasting
• Robust Kalman Filter Based on a Generalized Maximum-Likelihood-Type Estimator
• Recursive maximum likelihood identification method for a multivariable controlled autoregressive moving average system
• Filtering With Heavy Tails
• Dynamic Linear Models with R
• Kalman state filtering based least squares iterative parameter estimation for observer canonical state space systems using decomposition

This page was built for publication: Robust estimation of linear state space models