[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
"Martin Weiss" <martin.weiss1@gmx.de> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
AW: st: RE: mean of a distribution |

Date |
Sun, 18 Oct 2009 20:53:35 +0200 |

<> You can of course have Stata draw random numbers from the exponential distribution and see whether the relationships holds: ************* capt prog drop myprog prog def myprog vers 10.1 syntax [,lambda(real 1)] qui{ drop _all set obs 10000 tempvar x gen `x'= (-1/`lambda')*log(runiform()) } su `x', mean di in r _n "Mean with lambda equal to " /* */ %2.1fc `lambda' " : " r(mean) end forv i=0.1(0.1)3{ myprog, lambda(`i') } ************* HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von carol white Gesendet: Sonntag, 18. Oktober 2009 20:36 An: statalist@hsphsun2.harvard.edu Betreff: Re: st: RE: mean of a distribution Thanks for all responses. I just wanted to find out how could one have calculated the mean for example of the exponential distribution if the mean were not known (inverse of lambda)? Or as Martin called it shortcut, if the shortcut were not known? Carol --- On Sun, 10/18/09, Nick Cox <n.j.cox@durham.ac.uk> wrote: > From: Nick Cox <n.j.cox@durham.ac.uk> > Subject: st: RE: mean of a distribution > To: statalist@hsphsun2.harvard.edu > Date: Sunday, October 18, 2009, 11:12 AM > Not sure what you're asking here. > > One way to think about this parameterisation, or any other, > is by using > dimensional analysis. The density of a univariate > distribution for x > must have units that are the reciprocal of the units of x. > It follows > that lambda has such units, and the mean, having the units > of x, must be > proportional to the reciprocal of lambda. That doesn't give > you the > proportionality constant of 1, which follows from the rest > of the > definition, but it makes the reciprocation intuitive. > > David Finney wrote a splendid article about dimensional > analysis and > statistics: > > D. J. Finney. 1977. > Dimensions of statistics. > Journal of the Royal Statistical Society. Series C (Applied > Statistics), > 26: 285-289. > > This is on JSTOR, if you have access to that. > > Nick > n.j.cox@durham.ac.uk > > > carol white > > How to calculate the mean of the distribution of a random > variable? Take > the exponential distribution with the probability density > function > f(x)=lambda.exp(-lambda.x) where lambda is a constant and x > is a random > variable. The mean of this distribution is the reciprocal > of lambda. If > the mean is the expected value of x, which for a continuous > random > variable E(x) = Integral (x.f(x))dx, how could E(x) be the > reciprocal of > lambda? > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: RE: mean of a distribution***From:*carol white <wht_crl@yahoo.com>

- Prev by Date:
**RE: st: RE: mean of a distribution** - Next by Date:
**st: infixing numbers in exponential format** - Previous by thread:
**RE: st: RE: mean of a distribution** - Next by thread:
**st: infixing numbers in exponential format** - Index(es):

© Copyright 1996–2016 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |