Minimax robust designs for regression models with heteroscedastic errors
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DOI: 10.1007/s00184-021-00827-0
Abstract: Minimax robust designs for regression models with heteroscedastic errors are studied and constructed. These designs are robust against possible misspecification of the error variance in the model. We propose a flexible assumption for the error… read more here.
Keywords: robust designs; minimax robust; regression models; heteroscedastic errors ... See more keywords
Misspecified and Asymptotically Minimax Robust Quickest Change Detection
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2017.2740202
Abstract: We investigate the quickest detection of an unknown change in the distribution of a stochastic process generating independent and identically distributed observations. We develop new bounds on the performance of misspecified cumulative sum (CUSUM) rules,… read more here.
Keywords: quickest change; detection; robust quickest; change ... See more keywords