Grant: Discovery Grants Program - Accelerator Supplements
Université du Québec à Montréal
$40,000.00
High-dimensional problems for spatial point processes
FY 2019-20
Summary
concentration inequalities,high dimensional statistics,multiple testing problems,multivariate modellling,point processes,regularization techniques,sampling design,spatial statistics,statistical learning,stochstic geometry
Program
Discovery Grants Program - Accelerator Supplements
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
507945-2017
Name nom
Coeurjolly, JeanFrançois
Department département
Mathématiques
Organization id
57
Institution établissement
Université du Québec à Montréal
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2017
Award amount
40000
Program id
RGPAS
Program name en
Discovery Grants Program - Accelerator Supplements
Program name fr
Programme de subventions à la découverte - supplément d'accélération
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1559
Committee name en
DAS Selection Committee
Committee name fr
SAD Comité de sélection
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
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
Installment
inst:3 - 3
Partie
3
Nb partie
3
Application title
High-dimensional problems for spatial point processes
Keyword
NSERC
Application summary
concentration inequalities,high dimensional statistics,multiple testing problems,multivariate modellling,point processes,regularization techniques,sampling design,spatial statistics,statistical learning,stochstic geometry
