Given your starting values, there is nothing to optimize:
f - function(x, A=10, b=152, T=100, c=100) A*(1-exp(-b*(x-T) -
c*(sqrt(x) - sqrt(T
f(time)
[1] -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf
-Inf -Inf
[16] -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf
-Inf -Inf
[31] -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf -Inf
-Inf -Inf
[46] -Inf -Inf -Inf
same with A = 500
So try to find a better model, or more sensible starting values.
Regards, Sven
On 05/04/2012 03:41 PM, Silvano wrote:
Hi,
I need fit the France model :
y = A{1 - exp[-b(t-T) - c(sqrt(t) - sqrt(T))]}
parameters: A, b, T, c
variable: t (time)
resp: y
I tried:
time = 1:48
resp = rnorm(48, 200, 10)
dados = data.frame(resp, time)
attach(dados)
f = function(x, A, b, T, c)
A*(1-exp(-b*(x-T) - c*(sqrt(x) - sqrt(T
(mod1 = nls(resp~f(time, A, b, c, T), data=dados,
start=c(A=500, b=152, c=100, T=100)))
but isn't work. The error is:
(mod1 = nls(resp~f(tempo,A,b,c,T), data=dados,
+start=c(A=10, b=152, c=10, T=10)))
Erro em numericDeriv(form[[3L]], names(ind), env) :
Obtido valor faltante ou infinito quando avaliando o modelo
Somebody knows some package?
Thanks,
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