Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

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

From |
philippe van kerm <philippe.vankerm@ceps.lu> |

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

Subject |
st: RE: kernel density of values less than 1 |

Date |
Tue, 13 Jul 2010 08:39:50 +0200 |

If the support of your variable is [0,1], then it is not surprising that your density function goes >1. Remember that the density function has to integrate to 1. Philippe -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu [mailto:owner- > statalist@hsphsun2.harvard.edu] On Behalf Of Katja Hillmann > Sent: Monday, July 12, 2010 6:51 PM > To: statalist@hsphsun2.harvard.edu > Subject: st: kernel density of values less than 1 > > Hello, > > I used the command kdensity in order to calculate the density of > fractions (e.g. number of longterm unemployed on total unemployment). > Thus I try to calculate the denisty of values less than 1. However, the > values of the densities Stata provided are all greater than 1. Where is > the problem? Does Stata have problems in calculating distributions of > variables within an intervall of 0 and 1? > > Best, > Katja > * > * 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**:**st: kernel density of values less than 1***From:*Katja Hillmann <katja.hillmann@wiso.uni-hamburg.de>

- Prev by Date:
**AW: st: Tokenize local varlist** - Next by Date:
**st: AW: easier way to write many matrix names** - Previous by thread:
**Re: st: kernel density of values less than 1** - Next by thread:
**st: looping over observations in a single variable** - Index(es):