Hi R help, I am trying to determine how nls() generates a function based on the self-starting SSlogis and what the formula for the function would be. I've scoured the help site, and other literature to try and figure this out but I still am unsure if I am correct in what I am coming up with.
************************************************************************** dat <- c(75.44855206,NA,NA,NA,82.70745342,82.5335019,88.56617647,80.00128866,94.15418227,86.63987539,93.91052952,74.10612245,86.62289562,90.47961047,NA,NA,82.45320197,72.14371257,NA,71.44104803,72.59742896,68.36363636,NA,NA,61,NA,NA,71.26502909,NA,85.93333333,84.34248284,79.00522193,79.64223058,97.2074017,88.43700548,96.40413877,95.13511869,92.57379057,93.97498475,NA,97.55995131,89.53321146,97.21728545,93.21980198,77.54054054,95.85392575,86.25684723,97.55325624,80.03950617,NA,91.34023128,92.42906574,88.59433962,65.77272727,89.63772455,NA,NA,NA,NA,74.86344239,83.57594937,70.22516556,65.30543319,NA,NA,67.84852294,60.90909091,54.79303797,NA,52.18735363,33.47003155,NA,41.34693878,24.5047043,NA,NA,NA,NA,9.944444444,13.6875,NA,11.90267176,84.14285714,3.781456954,NA,1.432926829,4.26557377,1.823529412,0.444620253,4.711155378,NA,6.320284698,0.581632653,0.144578313,3.666666667,0,0,0,0,0,NA,0.032947462,0,0,10.54545455,0,NA,0.561007958,0.75,NA,0.048780488,0.74137931,NA,2.023339318,0,0,0,NA,NA,0.156950673,NA,0.283769634,32.81818182,NA,NA,0,NA,0,0,0,NA,0.212454212,3.120181406,NA,0.011811024,NA,0,0.120430108,5.928571429,1.75,0.679292929,0.97,NA,0,NA,NA,1,0.38547486,NA,1.460732984,0.007795889,0.05465288,0.004341534) dat.df.1 <- data.frame(dat) dat.df.2 <- data.frame(x=x.seq, dat.df=dat.df.1) fit.dat <-nls(dat ~ SSlogis(x, Asym, xmid,scal), data = dat.df.2, start =list(Asym=90, xmid = 75, scal = -6)) plot(dat.df.2, axes=FALSE, ann=FALSE, ylim=c(0,100)) lines(dat.df.2$x[complete.cases(dat.df.2)], predict(fit.dat), ylim=c(0,100)) summary(fit.dat) ************************************************************************** Formula: dat ~ SSlogis(x, Asym, xmid, scal) Parameters: Estimate Std. Error t value Pr(>|t|) Asym 85.651 1.716 49.900 < 2e-16 *** xmid 72.214 1.036 69.697 < 2e-16 *** scal -6.150 0.850 -7.236 7.9e-11 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 10.33 on 105 degrees of freedom Number of iterations to convergence: 10 Achieved convergence tolerance: 4.405e-06 (45 observations deleted due to missingness) ************************************************************************** >From r-help, SSlogis parameters asym, xmid and scal are defined as: Asym: a numeric parameter representing the asymptote. xmid: a numeric parameter representing the x value at the inflection point of the curve. The value of SSlogis will be Asym/2 at xmid. scal: a numeric scale parameter on the input axis. and it states that the value of SSlogis "is a numeric vector of the same length as input. It is the value of the expression sym/(1+exp((xmid-input)/scal)). If all of the arguments Asym, xmid, and scal are names of objects the gradient matrix with respect to these names is attached as an attribute named gradient." However, how do I get the actual function for the curve that is generated? I don't think it can just be: y= asym/((1+e^((xmid-x)/scal)))? Also, how do you determine the starting parameters to input in for asym, xmin, and scal? Perhaps I need to start at the beginning and define my own function, and not rely on SSlogis to provide it? What I want to be able to do is determine a local maximum for my curve (the x value at which this curve inflects (the upper inflection)), and the x value for the local minimum (the lower inflection curve), and the x value counts in between these values. I think in order to do this I need to differentiate the function. Any insight on this would be greatly appreciated. Sincerely, Katrina ______________________________________________ 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.
