On 10/28/13 00:10, Hansol Yu wrote:
data(Boston, package='MASS')
y <- Boston$nox
x <- Boston$dis
nls(y~ A + B * exp(C * x), start=list(A=1, B=1, C=1))
Error in nls(y ~ A + B * exp(C * x), start = list(A = 1, B = 1, C = 1), :
step factor 0.000488281 reduced below 'minFactor' of 0.000976562
I
On Apr 11, 2012, at 16:51 , John C Nash wrote:
> nls() often gives this message, which is misleading in that it is the
> Jacobian that is not
> of full rank in the solution of J * delta ~ - residuals or in more
> conventional
> Gauss-Newton J' * J delta = -g = - J' * residuals. My view is
nls() often gives this message, which is misleading in that it is the Jacobian
that is not
of full rank in the solution of J * delta ~ - residuals or in more
conventional
Gauss-Newton J' * J delta = -g = - J' * residuals. My view is that the
gradient itself
cannot be "singular". It's just
On Apr 10, 2012, at 22:03 , nerak13 wrote:
> Hi,
>
> I've got the following data:
>
> x<-c(1,3,5,7)
> y<-c(37.98,11.68,3.65,3.93)
> penetrationks28<-dataframe(x=x,y=y)
>
> now I need to fit a non linear function so I did:
>
> fit <- nls(y ~ I(a+b*exp(1)^(-c * x)), data = penetrationks28, star
On Apr 10, 2012, at 4:03 PM, nerak13 wrote:
Hi,
I've got the following data:
x<-c(1,3,5,7)
y<-c(37.98,11.68,3.65,3.93)
penetrationks28<-dataframe(x=x,y=y)
now I need to fit a non linear function so I did:
fit <- nls(y ~ I(a+b*exp(1)^(-c * x)), data = penetrationks28, start =
list(a=0,b = 1,
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