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Central Limit Theorem: Using the C.L.T. (modified R. Bloom)
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Statistics
The Quantile Function
(m23385)
Author:
Paul E Pfeiffer
Keywords:
Independent classes
,
Matlab procedures
,
Normal distribution
,
Properties
,
Random number generator
,
Sampling
,
Simple random variables
,
Weibull distribution
Summary:
If F is a probability distribution function, the associated quantile function Q is essentially an inverse of F. The quantile function is defined on the unit interval (0,1). For F continuous and strictly increasing at t, then Q(u)=t iff F(t)=u. Thus, if u is a ... quantile functions.
[Expand Summary]
If F is a probability distribution function, the associated quantile function Q is essentially an inverse of F. The quantile function is defined on the unit interval (0,1). For F continuous and strictly increasing at t, then Q(u)=t iff F(t)=u. Thus, if u is a probability value, t=Q(u) is the value of t for which P(X≤t)=u. As an application, one may generate independent classes with prescribed distributions. Matlab procedures are developed for a variety of problems involving quantile functions.
[Collapse Summary]
Subject:
Mathematics and Statistics
Language:
English
Popularity:
92.10%
Revised:
20090918
Revisions:
7
Popularity is measured as percentile rank of page views/day over all time
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