Dear all, I''d like to use the `SSweibull'' function for survival analysis. In order to become acquainted with the function, I said `help(SSweibull)'' and went through the example. What puzzles me is 1. What should I make of the assertion `Initial values are in fact the converged values''? 2. When doing a `SSweibull(Chick.6$Time, Asym, Drop, lrc, pwr)'' I can see no indication of convergence of the values whatsoever. On the other hand, plotting the object yields a nice Weibull curve. 3. Wouldn''t it be nice to have some formulas in the help section precisely explaining the meaning of the parameters? There are several parametrizations of the Weibull distribution. Cheers, Mirko. -- Dr. M. Luedde <Mirko.Luedde at CellControl.De> CellControl Biomedical Laboratories AG Am Klopferspitz 19, 82152 Martinsried +49-89-895275-0 +49-179-5252064 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
On Tue, 26 Jun 2001, [ISO-8859-1] Lüdde Mirko wrote:> Dear all, > > I''d like to use the `SSweibull'' function for survival analysis. InYou would be better off using survreg in package survival (formerly survival5). You forgot to mention SSweibull is in package nls, BTW, and intended to be used by a call to nls().> order to become acquainted with the function, I said `help(SSweibull)'' > and went through the example. What puzzles me is > > 1. What should I make of the assertion `Initial values are in fact the > converged values''? > > 2. When doing a `SSweibull(Chick.6$Time, Asym, Drop, lrc, pwr)'' > I can see no indication of convergence of the values whatsoever. > On the other hand, plotting the object yields a nice Weibull curve. > > 3. Wouldn''t it be nice to have some formulas in the help section > precisely explaining the meaning of the parameters? There > are several parametrizations of the Weibull distribution.Would you like to submit a patch to the help page (to R-bugs)? You can read the R code to find out which was used, or even the help page under Value:!> > Cheers, Mirko. > -- > Dr. M. Luedde <Mirko.Luedde at CellControl.De> > CellControl Biomedical Laboratories AG > Am Klopferspitz 19, 82152 Martinsried > +49-89-895275-0 +49-179-5252064 > -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- > r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html > Send "info", "help", or "[un]subscribe" > (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch > _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._ >-- Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272860 (secr) Oxford OX1 3TG, UK Fax: +44 1865 272595 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Dear Prof Ripley, there was no (direct) answer to any of my questions in your post, but I think I''m getting the idea! Sorry for my ignorance. And I still seem to have a gross misunderstanding about the use of `SSweibull(nls)''. Is it simply a means to calculate the Weibull distribution? What''s the difference to `pweibull'', then? Which means could help me estimating the Weibull parameters from empirical data? And what does it mean that `[SSweibull is] intended to be used by a call to nls()''? Thanks for your patience, Mirko. -- Dr. M. Luedde business: CellControl AG, Am Klopferspitz 19, 82152 Martinsried, +49-89-895275-0, Mirko.Luedde at CellControl.De private: Godehardsplatz 16, 31134 Hildesheim, +49-179-5252064, Mirko.Luedde at Computer.Org -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
On Tue, 26 Jun 2001, Dr. Mirko Luedde wrote:> Dear Prof Ripley, > > there was no (direct) answer to any of my questions in your post, but > I think I''m getting the idea! Sorry for my ignorance. > > And I still seem to have a gross misunderstanding about the use of > `SSweibull(nls)''. > > Is it simply a means to calculate the Weibull > distribution? > > What''s the difference to `pweibull'', then? > > Which means could help me estimating the Weibull parameters from > empirical data?The survreg() function in the survival package fits Weibull distributions (and accelarated failure models) to (possibly censored) data, that is if your data have a Weibull distribution. This is a location-scale model parametrised so that (log(y)-mu)/scale has the cdf 1-exp(-exp(y)), the natural accelerated failure parametrisation rather than the proportional hazards one. SSweibull is designed to help with fitting the Weibull growth curve model to empirical data. This is not the same as fitting a Weibull distribution. SSweibull is a self-starting (thus the SS) model for use with nls(). That is, nls() allows you to fit complicated nonlinear models, most of which require good starting estimates of parameters. The self-starting models can guess good starting values for nls(). -thomas Thomas Lumley Asst. Professor, Biostatistics tlumley at u.washington.edu University of Washington, Seattle -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Dr. Mirko Luedde wrote:>Dear Prof Ripley,>there was no (direct) answer to any of my questions in your post, but >I think I''m getting the idea! Sorry for my ignorance.I take the liberty to answer to these questions. Prof Ripley has certainly many work answering questions about 1.3.0 installation and so on... but I am sure he will add some nice tip to this answer if required.>And I still seem to have a gross misunderstanding about the use of >`SSweibull(nls)''.SSweibull, like any Self-starting function in R (SSlogis, SS...) is just an analytical function y = f(x) that returns y values for provided x values. Under some circumstances, it returns also the gradient matrix, i.e.: the Jacobian or if you prefer the matrix of partial derivatives according to each parameters of the function. See ?SSweibull for more info. The equation is provided. It is: Asym-Drop*exp(-exp(lrc)*x^pwr), with Asym, Drop, lrc and pwr being parameters to estimate.>Is it simply a means to calculate the Weibull >distribution?No. See answer to the previous question.>What''s the difference to `pweibull'', then?Idem.>Which means could help me estimating the Weibull parameters from >empirical data?>And what does it mean that `[SSweibull is] intended to be used by a >call to nls()''?Self-starting objects are mostly intended to define a formula like y ~ SSweibull(x, Asym, Drop, lrc, pwr). This formula is used as first argument of the nonlinear least-square regression function that evaluate parameters from empirical data. See last line of example in the SSweibull help. It will create a nls object with all you need to diagnose the fitting. Use summary(nlsobjectname) for instance. Usually with nls(), you also have to provide initial guess of parameters, and convergence is dependent upon these initial guess. To ease the use of nls(), Self-starting functions have a nice algorithm that evaluate good guess for intial values of parameters and you don''t need to provide them. Many Self-starting functions of nls() library even got the parameters estimation that correspond to the overall minima of the obective function. In this case, initial evaluation _is_ also evaluation at convergence and it is fast, easy, and secure (you are sure it is not just a local minimum). Please, note thate library nlrq uses the same Self-starting functions than nls(), but performs nonlinear quantile regression which could be useful for study of survival (calculating curves corresponding to various quantiles, see ?nlrq and the corresponding paper citer in help). Otherwise, I am sure you will find very good stuff in survreg... but there I cannot help you. Regards, Philippe Grosjean ...........]<(({?<...............<?}))><............................... ) ) ) ) ) __ __ ( ( ( ( ( |__) | _ ) ) ) ) ) | hilippe |__)rosjean ( ( ( ( ( Marine Biol. Lab., ULB, Belgium ) ) ) ) ) __ ( ( ( ( ( |\ /| |__) ) ) ) ) ) | \/ |ariculture & |__)iostatistics ( ( ( ( ( ) ) ) ) ) e-mail: phgrosje at ulb.ac.be or phgrosjean at sciviews.org ( ( ( ( ( SciViews project coordinator (http://www.sciviews.org) ) ) ) ) ) tel: 00-32-2-650.29.70 (lab), 00-32-2-673.31.33 (home) ( ( ( ( ( ) ) ) ) ) "I''m 100% confident that p is between 0 and 1" ( ( ( ( ( L. Gonick & W. Smith (1993) ) ) ) ) ) ....................................................................... -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._