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From |
"Conner Mullally" <[email protected]> |

To |
[email protected] |

Subject |
Re: st: evaluating probabilities using kdensity |

Date |
Mon, 03 Mar 2008 05:35:28 -0800 |

Thanks for the help. I think I could have been more specific about exactly what I am trying to do. I have 20 years of time series, which I have detrended. What I want to do is to: a) Take the detrended time series and estimate a kernel density b) Use the estimated kernel density to estimate the expected value of shortfalls from the mean of the distribution. That is, I want to calculate the integral of: (Mu-Yt)dF(Yt)dYt, for all Yt<Mu Where Mu is the mean, Yt is the random variable, and F(Yt) is the cumulative density function of Yt. The command kdensity returns the estimated density at whatever points were used to estimate the density, and I can add more points using the at() option. But these will leave gaps at the omitted points in the support of the estimated distribution when I sum up the densities. What I'm wondering is if there is a way to integrate under the curve of the estimated kernel density. Perhaps some stata programming is in my future, but if there is way to do this while using kdensity or something similar, I would love to know. Thanks in advance. * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: evaluating probabilities using kdensity***From:*Maarten buis <[email protected]>

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