In statistics, the concept of a concomitant, also called the induced order statistic, arises when one sorts the members of a random sample according to corresponding values of another random sample. Let (Xi, Yi), i = 1, . . ., n be a random sample from a bivariate distribution. If the sample is ordered by the Xi, then the Y-variate associated with Xr:n will be denoted by Y[r:n] and termed the concomitant of the rth order statistic. If all are assumed to be i.i.d., then for , the joint density for is given by
Attributes | Values |
---|
rdfs:label
| - Concomitant (statistics) (en)
|
rdfs:comment
| - In statistics, the concept of a concomitant, also called the induced order statistic, arises when one sorts the members of a random sample according to corresponding values of another random sample. Let (Xi, Yi), i = 1, . . ., n be a random sample from a bivariate distribution. If the sample is ordered by the Xi, then the Y-variate associated with Xr:n will be denoted by Y[r:n] and termed the concomitant of the rth order statistic. If all are assumed to be i.i.d., then for , the joint density for is given by (en)
|
dcterms:subject
| |
Wikipage page ID
| |
Wikipage revision ID
| |
Link from a Wikipage to another Wikipage
| |
sameAs
| |
dbp:wikiPageUsesTemplate
| |
has abstract
| - In statistics, the concept of a concomitant, also called the induced order statistic, arises when one sorts the members of a random sample according to corresponding values of another random sample. Let (Xi, Yi), i = 1, . . ., n be a random sample from a bivariate distribution. If the sample is ordered by the Xi, then the Y-variate associated with Xr:n will be denoted by Y[r:n] and termed the concomitant of the rth order statistic. Suppose the parent bivariate distribution having the cumulative distribution function F(x,y) and its probability density function f(x,y), then the probability density function of rth concomitant for is If all are assumed to be i.i.d., then for , the joint density for is given by That is, in general, the joint concomitants of order statistics is dependent, but are conditionally independent given for all k where . The conditional distribution of the joint concomitants can be derived from the above result by comparing the formula in marginal distribution and hence (en)
|
prov:wasDerivedFrom
| |
page length (characters) of wiki page
| |
foaf:isPrimaryTopicOf
| |
is Link from a Wikipage to another Wikipage
of | |
is Wikipage disambiguates
of | |
is foaf:primaryTopic
of | |