On Nov 17, 2011, at 4:40 PM, Katrina Bennett wrote:
Hello, I am wondering if someone can help me. I have the following
function
that I derived using nls() SSlogis. I would like to find its
derivative. I
thought I had done this using deriv(), but for some reason this isn't
working out for me.
Here is the function:
asym <- 84.951
xmid <- 66.90742
scal <- -6.3
x.seq <- seq(1, 153,, 153)
nls.fn <- asym/((1+exp((xmid-x.seq)/scal)))
try #1
deriv(nls.fn)
#get an Error in .Internal(deriv.default(expr, namevec,
function.arg, tag,
hessian)) : 'namevec' is missing
try #2
deriv(nls.fn, namevec=c("asym", "xmid", "scal"))
#this doesn't seem to give me the expression, and the gradients are
zero.
nls.fn is not a function or an expression. It has been evaluated and
now it's a vectpr, and not what `deriv` is "expecting". If you want to
use `deriv` or `D` you must first read the help page:
?deriv
And then construct a proper expresssion, call, or function...
> nls.expr <- expression( 84.951/((1 + exp(( 66.90742- x)/ -6.3))) )
> D(nls.expr, "x")
-(84.951 * (exp((66.90742 - x)/-6.3) * (1/6.3))/((1 + exp((66.90742 -
x)/-6.3)))^2)
> deriv(nls.expr, "x")
expression({
.expr4 <- exp((66.90742 - x)/-6.3)
.expr5 <- 1 + .expr4
.value <- 84.951/.expr5
.grad <- array(0, c(length(.value), 1L), list(NULL, c("x")))
.grad[, "x"] <- -(84.951 * (.expr4 * (1/6.3))/.expr5^2)
attr(.value, "gradient") <- .grad
.value
})
--
David.
I've tried to do this with Ryacas as well, but I'm lost.
Can anyone help?
Thank you,
Katrina
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and provide commented, minimal, self-contained, reproducible code.
