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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Xaxis transformation after logging variable |

Date |
Tue, 21 Aug 2012 17:00:05 +0100 |

Of your three references here, one is now recognisable to me as a paper in Biometrika. The others ring no bells without details. The parameterisation details make little sense without any definitions or formulas. It's possible that this distribution is a reparameterisation of one that can be fitted with code by Stephen Jenkins with/without coauthors. I suppress full references to underline what you are (not) doing here. Otherwise, I advise reposting. Before you do that, please do read the Statalist FAQ. Nick On Tue, Aug 21, 2012 at 4:24 PM, Francisco Augusto <francisco.augusto.7@gmail.com> wrote: > Thanks for the quick answer. It worked! (I am sorry for the trivial > question, though) > > The reference I was talking about was Nick Cox, Speaking Stata: > Graphing Distributions, 2004, The Stata Journal, pp 77 > > For the other question, I am sorry for the lack of information. > > I am trying to use the Prentice 1974 "A log gamma model and its > maximum likelihood estimation" Biometrika Trust. In this approach the > parameter k is transformed to q = k ^ (-1/2) with support to k of 0 > to +infinity , parametrization also used by Lawless 1980 "Inference in > the generalized gamma and log gamma Distributions" and applied in > Cabral & Mata 2003 "On evolution of firm size distribution: facts and > theory". > > With this approach I intended to apply the extended generalized gamma > distribution to the logged variable, and by that obtaining estimates > for the different parameters. After that, I was trying to regress the > logged variable on other variables assuming the logged variable > follows the extended generalized distribution. > > Should I "repost" the previous question? Is this information enough? > > Thank you very much for all the help, > Francisco Augusto > > > > > On Tue, Aug 21, 2012 at 3:50 PM, Nick Cox <njcoxstata@gmail.com> wrote: >> "Cox showed" (even guessing and narrowing it down to me) is not a >> precise reference. But if your axis variable is log_10(variable) and >> you want labels in terms of variable, you can just go something like >> >> ... xla(0 "1" 1 "10" 2 "100") >> >> This is well documented at -help axis label options- and is no sense >> limited to showing kernel density estimates. >> >> I guess people ignored your previous question because it wasn't clear >> (there are several possible generalisations oof the gamma >> distribution) and was based on an incomplete reference. Still true. >> >> Nick >> >> On Tue, Aug 21, 2012 at 3:27 PM, Francisco Augusto >> <francisco.augusto.7@gmail.com> wrote: >>> Dear Statalist, >>> >>> I am dealing with a small problem: I am doing kernel (kdensity) of a >>> logged variable and I would like to rearrange the Xaxis to be in the >>> original scale and on a 10 exponential order (like 1 10 100 1000 >>> 10000, of the original values). I have seen a solution for the first >>> part of the problem: Cox showed a command to get the original scale on >>> the xaxis after logging a variable. Nevertheless, I don't know how to >>> have the 1 10 100 1000 10000 order. >>> >>> Plus, I am still struggling to find a solution for the Prentice 1974 >>> generalized gamma approach. It would be so nice for someone to present >>> a possible solution! * * 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/

**Follow-Ups**:**Re: st: Xaxis transformation after logging variable***From:*Francisco Augusto <francisco.augusto.7@gmail.com>

**References**:**st: Xaxis transformation after logging variable***From:*Francisco Augusto <francisco.augusto.7@gmail.com>

**Re: st: Xaxis transformation after logging variable***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: Xaxis transformation after logging variable***From:*Francisco Augusto <francisco.augusto.7@gmail.com>

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