curve fitting
or use nls.lm as in
install.packages("minpack.lm")
library(minpack.lm)
x <- c(2, 8, 14, 20, 26, 32, 38, 44, 50, 56, 62, 68, 74)
y <- c(100, 99, 99, 98, 97, 94, 82, 66, 48, 38, 22, 10, 1)
res <- function(p, x, y) y - ff(p,x)
ff <- function(p, x) 100*exp(p[1]*(1-exp(p[2]*x))/p[2])
aa <- nls.lm(par=c(.0001,.0001), fn=res, x=x, y=y)
plot(x,y)
lines(x, ff(coef(aa), x))
On Tue, 12 May 2009, Jorge Ivan Velez wrote:
Dear Dmitry, Take a look at ?nls and its examples. HTH, Jorge On Tue, May 12, 2009 at 5:44 PM, Dmitry Gospodaryov <gospodaryov at rambler.ru>wrote:
I have the data: for x: 2, 8, 14, 20, 26, 32, 38, 44, 50, 56, 62, 68, 74, for y: 100, 99, 99, 98, 97, 94, 82, 66, 48, 38, 22, 10, 1. y depends on x by equation: y = 100*exp(b*(1-exp(c*x))/c), where b and c are coefficients. I need to find coefficients in this equation for given data. How can I do that by means of R? Thank you for advance. With regard, Dmitry.
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______________________________________________ R-help at 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.