Dear all, I've used glm(family=binomial(link="logit")) several times, but now I think that a log link is more appropriate.
I want to fit a model for probability of tree fall (TF)), with tree diameter (dbh) and soil moisure (soil) as predictors. A large number of trees have been checked every second year whether they stand up (0) or have fallen (1). I assume that the tree fall probability is predicted by TF = 1 - exp(-(dbh + soil)) log(1 - TF) = -(dbh + soil) I thought the following call would fit the model, but I get an error message. test<- glm(1-TF ~ dbh +soil , data = extdat, family = quasibinomial(link = "log")) Error: no valid set of coefficients has been found:please supply starting values In addition: Warning message: NaNs produced in: log(x) Could someone give a clue on what is wrong. Is there another way to fit this model? People have asked about exponential models before but they have dealt with continuous responses. Thanks in advance! Yours sincerely, Tord ----------------------------------------------------------------------- Tord Snäll Avd. f växtekologi, Evolutionsbiologiskt centrum, Uppsala universitet Dept. of Plant Ecology, Evolutionary Biology Centre, Uppsala University Villavägen 14 SE-752 36 Uppsala, Sweden Tel: 018-471 28 82 (int +46 18 471 28 82) (work) Tel: 018-25 71 33 (int +46 18 25 71 33) (home) Fax: 018-55 34 19 (int +46 18 55 34 19) (work) E-mail: [EMAIL PROTECTED] Check this: http://www.vaxtbio.uu.se/resfold/snall.htm! ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
