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Grant: Discovery Grants Program - Individual

McMaster University

$68.00

Non-Gaussian Model-Based Clustering

FY 2014-15

Summary
Contemporary science research is confronted with ever-growing masses of data. Given that scientists rely on statistics to interpret results, the availability of suitable statistical methods is essential. Unfortunately, some research questions cannot currently be answered due to the lack of appropriate statistical techniques. The proposed research will develop novel approaches to the assembly of data into groups; such approaches are known as clustering or classification. These techniques, once developed, will be released for use by researchers in every discipline through packages for the R software. The impact of this work will be felt in disciplines such as bioinformatics, where it will help identify genes that behave in a similar fashion either in general or over the time course of some experiment. There will also be real impact in other areas such as food science and sociology.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
356040-2012
Name nom
McNicholas, Paul
Department département
Mathematics and Statistics
Organization id
27
Institution établissement
McMaster University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2014
Competition year année de concours
2012
Award amount
68
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1508
Committee name en
Mathematics and Statistics
Committee name fr
Mathématiques et statistique
Area of application code
1201
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Life sciences (including biotechnology)
Area of application fr
Sciences de la vie (y compris biotechnologie)
Research subject code
3000
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Statistics and probability
Research subject fr
Statistique et probabilité
Partie
3
Nb partie
5
Application title
Non-Gaussian Model-Based Clustering
Keyword
NSERC
Application summary
Contemporary science research is confronted with ever-growing masses of data. Given that scientists rely on statistics to interpret results, the availability of suitable statistical methods is essential. Unfortunately, some research questions cannot currently be answered due to the lack of appropriate statistical techniques. The proposed research will develop novel approaches to the assembly of data into groups; such approaches are known as clustering or classification. These techniques, once developed, will be released for use by researchers in every discipline through packages for the R software. The impact of this work will be felt in disciplines such as bioinformatics, where it will help identify genes that behave in a similar fashion either in general or over the time course of some experiment. There will also be real impact in other areas such as food science and sociology.
McMaster University - $68 Grant (2014-15) | Canada Spends