Grant: Discovery Grants Program - Individual
Concordia University
$15,000.00
An eigenfunction approach to multivariate and high-dimensional survival analysis
EF 2021-22
Résumé
cure-rates; eigenfunctions and eigenvectors; empirical likelihood; model checking; multivariate hazard measure; multivariate random censoring; multivariate random truncation; regression; survival forests; two sample tests
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2016-05722
Name nom
Sen, Arusharka
Department département
Mathematics and Statistics
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2021
Competition year année de concours
2016
Award amount
15000
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
1205
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Mathematical sciences
Area of application fr
Sciences mathématiques
Research subject code
3011
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Multivariate analysis
Research subject fr
Analyse multivariée
Installment
inst:6
Partie
1
Nb partie
6
Application title
An eigenfunction approach to multivariate and high-dimensional survival analysis
Keyword
NSERC
Application summary
cure-rates; eigenfunctions and eigenvectors; empirical likelihood; model checking; multivariate hazard measure; multivariate random censoring; multivariate random truncation; regression; survival forests; two sample tests
