Grant: Discovery Grants Program - Individual
St. Francis Xavier University
$8,000.00
Ordered ranked set sample and applications to statistical inference
EF 2006-07
Résumé
Cost-effective sampling methods are of major concern in statistics. Ranked set sampling (RSS) was first proposed in 1952. After being forgotten for quite a while, the value of RSS was rediscovered in recent years because of its cost-effective nature. Now, RSS method attracts practical interest in areas such as agriculture, forestry, ecological science, environmental science, and even medical studies. Until recently, the publications and research about ranked set sampling are based on ranked set sample itself or on asymptotical properties of order statistics of ranked set sample. But in some practical problems, the order statistics of RSS (ORSS) other than the RSS itself are desired. In the past few years, we successfully derived the distribution of ORSS, and applied it to somce statistical inferences. Part of this proposal is to keep the momentum and to explore more applications of ORSS to statistical inference. Moreover, we will generalize our work to imperfect ranking, which is more suitable for practical problems.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Nova Scotia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
327517-2006
Name nom
Li, Tao
Department département
Mathematics, Statistics & Computing Sciences
Organization id
83
Institution établissement
St. Francis Xavier University
Province en
Nova Scotia
Province fr
Nouvelle-Écosse
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2006
Competition year année de concours
2006
Award amount
8000
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
14
Committee name en
Statistical Sciences
Committee name fr
Statistique
Area of application code
201
Area of application group en
Natural resources (economic aspects)
Area of application group fr
Ressources naturelles (aspects économiques)
Area of application en
Forestry (silviculture, forest management)
Area of application fr
Foresterie (sylviculture, aménagement forestier)
Research subject code
3001
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Statistical theory
Research subject fr
Théorie de statistique
Partie
1
Nb partie
3
Application title
Ordered ranked set sample and applications to statistical inference
Keyword
NA
Application summary
Cost-effective sampling methods are of major concern in statistics. Ranked set sampling (RSS) was first proposed in 1952. After being forgotten for quite a while, the value of RSS was rediscovered in recent years because of its cost-effective nature. Now, RSS method attracts practical interest in areas such as agriculture, forestry, ecological science, environmental science, and even medical studies. Until recently, the publications and research about ranked set sampling are based on ranked set sample itself or on asymptotical properties of order statistics of ranked set sample. But in some practical problems, the order statistics of RSS (ORSS) other than the RSS itself are desired. In the past few years, we successfully derived the distribution of ORSS, and applied it to somce statistical inferences. Part of this proposal is to keep the momentum and to explore more applications of ORSS to statistical inference. Moreover, we will generalize our work to imperfect ranking, which is more suitable for practical problems.
