A review on robust M-estimators for regression analysis

Data reconciliation in the Quality-by-Design (QbD) implementation of pharmaceutical continuous tablet manufacturing

(2019) Qinglin Su et al.   INTERNATIONAL JOURNAL OF PHARMACEUTICS

Robust state estimation of feeding–blending systems in continuous pharmaceutical manufacturing

(2018) Jianfeng Liu et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

Approaches to robust process identification: A review and tutorial of probabilistic methods

(2018) Hariprasad Kodamana et al.   JOURNAL OF PROCESS CONTROL

Development of robust extended Kalman filter and moving window estimator for simultaneous state and parameter/disturbance estimation

(2018) Jayaram Valluru et al.   JOURNAL OF PROCESS CONTROL

A novel robust data reconciliation method for industrial processes

(2018) Sen Xie et al.   CONTROL ENGINEERING PRACTICE

Classification of Systematic Measurement Errors within the Framework of Robust Data Reconciliation

(2017) Claudia E. Llanos et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Maximum likelihood optimal and robust Support Vector Regression with lncosh loss function

(2017) Omer Karal   NEURAL NETWORKS

On-Line Dynamic Data Reconciliation in Batch Suspension Polymerizations of Methyl Methacrylate

(2017) Jamille Coimbra et al.   Processes

Robust data reconciliation of combustion variables in multi-fuel fired industrial boilers

(2016) Timo Korpela et al.   CONTROL ENGINEERING PRACTICE

Correntropy based data reconciliation and gross error detection and identification for nonlinear dynamic processes

(2015) Zhengjiang Zhang et al.   COMPUTERS & CHEMICAL ENGINEERING

Robust Estimators for Data Reconciliation

(2015) Claudia E. Llanos et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Comparison of methods for estimation of the covariance matrix of measurement errors

(2014) Thiago Feital et al.   CANADIAN JOURNAL OF CHEMICAL ENGINEERING

Methodology of data reconciliation and parameter estimation for process systems with multi-operating conditions

(2014) Zhengjiang Zhang et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Correntropy estimator for data reconciliation

(2013) Junghui Chen et al.   CHEMICAL ENGINEERING SCIENCE

A New Target Function for Robust Data Reconciliation

(2012) Siyi Jin et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Simultaneous Model Selection, Robust Data Reconciliation and Outlier Detection with Swarm Intelligence in a Thermal Reactor Power calculation

(2011) Eduardo Damianik Valdetaro et al.   ANNALS OF NUCLEAR ENERGY

Sharpening Wald-type inference in robust regression for small samples

(2011) Manuel Koller et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

The Changing History of Robustness

(2010) Stephen M. Stigler   AMERICAN STATISTICIAN

Simultaneous robust data reconciliation and gross error detection through particle swarm optimization for an industrial polypropylene reactor

(2010) Diego Martinez Prata et al.   CHEMICAL ENGINEERING SCIENCE

Nonlinear dynamic data reconciliation and parameter estimation through particle swarm optimization: Application for an industrial polypropylene reactor

(2009) Diego Martinez Prata et al.   CHEMICAL ENGINEERING SCIENCE

Quasi-weighted least squares estimator for data reconciliation

(2009) Zhengjiang Zhang et al.   COMPUTERS & CHEMICAL ENGINEERING

A new m-estimator based robust multiuser detection in flat-fading non-gaussian channels

(2009) T.A. Kumar et al.   IEEE TRANSACTIONS ON COMMUNICATIONS

Scaled steady state models for effective on-line applications

(2007) Tore Lid et al.   COMPUTERS & CHEMICAL ENGINEERING

Data reconciliation: A robust approach using a contaminated distribution

(2007) Moustapha Alhaj-Dibo et al.   CONTROL ENGINEERING PRACTICE

Data reconciliation and optimal operation of a catalytic naphtha reformer

(2007) Tore Lid et al.   JOURNAL OF PROCESS CONTROL

Robust estimate of excitations in mechanical systems using M-estimators—Theoretical background and numerical applications

(2007) Paolo Pennacchi   JOURNAL OF SOUND AND VIBRATION

Redescending M-estimators

(2007) Georgy Shevlyakov et al.   JOURNAL OF STATISTICAL PLANNING AND INFERENCE