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...
Main Authors: | , , , , , |
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Other Authors: | |
Format: | Text |
Language: | English |
Published: |
2005
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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 |
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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