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Farcomeni, A. & Greco, L. Robust Methods for Data Reduction CRC Presss, 2015).
He specializes in econometrics, and his research develops robust methods for inference on causal or structural relationships using economic data.
We suggest that the increase in the estimate is mainly explained by the use of more robust methods for quantifying macro- and megaplastics over larger sea surface areas.
This review examines important robust methods for sustained, steady-state, in vitro culture.
This is achieved by employing robust methods for the determination of modeling uncertainties.
Fast and robust methods for determination of the glycosylation patterns of therapeutic antibodies are therefore needed.
This book presents the design of novel and robust methods for capturing the semantics of natural language questions and for finding relevant text snippets.
However, there is a lack of robust methods for the globally optimal design of complex column sequences.
This research activity deals with robust methods for parameters estimation of nonlinear models and the outliers detection.
With ever-increasing data in the field of medical imaging, the availability of robust methods for quantitative analysis in large-scale studies is the need of the hour.
Interrogation of gene regulatory circuits in complex organisms requires precise tools for the selection of individual cell types and robust methods for biochemical profiling of target proteins.
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