# SSlogis

0th

Percentile

##### Self-Starting Nls Logistic Model

This selfStart model evaluates the logistic function and its gradient. It has an initial attribute that creates initial estimates of the parameters Asym, xmid, and scal. In R 3.4.2 and earlier, that init function failed when min(input) was exactly zero.

Keywords
models
##### Usage
SSlogis(input, Asym, xmid, scal)
##### Arguments
input

a numeric vector of values at which to evaluate the model.

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.

##### Value

a numeric vector of the same length as input. It is the value of the expression Asym/(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.

nls, selfStart
library(stats) # NOT RUN { Chick.1 <- ChickWeight[ChickWeight$Chick == 1, ] SSlogis(Chick.1$Time, 368, 14, 6) # response only local({ Asym <- 368; xmid <- 14; scal <- 6 SSlogis(Chick.1$Time, Asym, xmid, scal) # response _and_ gradient }) getInitial(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1) ## Initial values are in fact the converged one here, "Number of iter...: 0" : fm1 <- nls(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1) summary(fm1) ## but are slightly improved here: fm2 <- update(fm1, control=nls.control(tol = 1e-9, warnOnly=TRUE), trace = TRUE) all.equal(coef(fm1), coef(fm2)) # "Mean relative difference: 9.6e-6" str(fm2$convInfo) # 3 iterations # } # NOT RUN { <!-- %donttest --> # } # NOT RUN { dwlg1 <- data.frame(Prop = c(rep(0,5), 2, 5, rep(9, 9)), end = 1:16) iPar <- getInitial(Prop ~ SSlogis(end, Asym, xmid, scal), data = dwlg1) ## failed in R <= 3.4.2 (because of the '0's in 'Prop') stopifnot(all.equal(tol = 1e-6, iPar, c(Asym = 9.0678, xmid = 6.79331, scal = 0.499934))) ## Visualize the SSlogis() model parametrization : xx <- seq(-0.75, 5, by=1/32) yy <- 5 / (1 + exp((2-xx)/0.6)) # == SSlogis(xx, *): stopifnot( all.equal(yy, SSlogis(xx, Asym = 5, xmid = 2, scal = 0.6)) ) require(graphics) op <- par(mar = c(0.5, 0, 3.5, 0)) plot(xx, yy, type = "l", axes = FALSE, ylim = c(0,6), xlim = c(-1, 5), xlab = "", ylab = "", lwd = 2, main = "Parameters in the SSlogis model") mtext(quote(list(phi == "Asym", phi == "xmid", phi == "scal"))) usr <- par("usr") arrows(usr, 0, usr, 0, length = 0.1, angle = 25) arrows(0, usr, 0, usr, length = 0.1, angle = 25) text(usr - 0.2, 0.1, "x", adj = c(1, 0)) text( -0.1, usr, "y", adj = c(1, 1)) abline(h = 5, lty = 3) arrows(-0.8, c(2.1, 2.9), -0.8, c(0, 5 ), length = 0.1, angle = 25) text (-0.8, 2.5, quote(phi)) segments(c(2,2.6,2.6), c(0, 2.5,3.5), # NB. SSlogis(x = xmid = 2) = 2.5 c(2,2.6,2 ), c(2.5,3.5,2.5), lty = 2, lwd = 0.75) text(2, -.1, quote(phi)) arrows(c(2.2, 2.4), 2.5, c(2.0, 2.6), 2.5, length = 0.08, angle = 25) text( 2.3, 2.5, quote(phi)); text(2.7, 3, "1") par(op) # }