Hello, I'm trying to fit a logistic curve to data but I'm having a hard time discovering how. Every tutorial I've come across either assumes the logistic curve has 0<y<1 or assumes I have multiple categories of data
I simply have two vectors, a and b, of equal length with no missing data, and I suspect they follow a logistic curve. The vectors are a<-c(39609, 39643, 39700, 39829, 39889, 39926, 40008, 40084, 40183, 40276, 40297, 40336, 40422, 40471, 40565, 40700, 40731, 40820, 40971, 41071, 41205) b<-c(0,10000000, 100000000, 500000000, 800000000, 1000000000, 1500000000, 2000000000, 3000000000, 4000000000, 4500000000, 5000000000, 6500000000, 7000000000, 10000000000, 14000000000, 15000000000, 18000000000, 25000000000, 30000000000, 35000000000) How do I find the best-fit logistic curve for this data in R? - J PS: The tutorials I mentioned are http://www.apsnet.org/EDCENTER/ADVANCED/TOPICS/ECOLOGYANDEPIDEMIOLOGYINR/DISEASEPROGRESS/Pages/NonlinearRegression.aspx, which assumes I have multiple categories of data, and http://ww2.coastal.edu/kingw/statistics/R-tutorials/logistic.html which only accepts y between 0 and 1. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
