Kuopio, Finland M-estimation Applied to Bioaffinity Data

The aim of this research is to estimate the statistics describing the data using low sample size. Data consisted of bioaffinity measurements carrying information on analyte type and concentration. Measurements were performed by Arctic Diagnostics using ArcDia TPX technique. Due to noise contaminatio...

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Bibliographic Details
Main Authors: Mikko Västilä, Sari Peltonen, Edisson Albán, Jori Soukka, Juhani T. Soini, Ulla Ruotsalainen
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2005
Subjects:
Arctic
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.216.4988
http://www.cs.uku.fi/finsig05/papers/paper10_FINSIG05.pdf
Description
Summary:The aim of this research is to estimate the statistics describing the data using low sample size. Data consisted of bioaffinity measurements carrying information on analyte type and concentration. Measurements were performed by Arctic Diagnostics using ArcDia TPX technique. Due to noise contamination (e.g. outliers) of the data, robust estimation methods were applied, particularly redescending type of M-estimators, which are able to completely reject deviating observations. Experimental results clearly show benefits of robust estimation methods when measurements deviate from commonly assumed models, e.g. normal distribution. 1.

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