Hi,
I am trying to fit experimental points by exponemtial curve
my data are stored into a matrix data
the first column is the geographical point (a number = data[,1] ) ( I
would like to plot several graphes at the same time)
the second column is the time of measurement (x in the plot)
the third column is a speed (y in the plot)
if we assume the point are folowing this exponential behaviour y=exp(a+bx)
then log y = a+ bx
we then can determine the coefficient a and b by a linear regression with
the lm function and get them as following : coef ( lm (log(y)~x))
then I can use those coefficient
if I plot ln y = ax+b , everything goes fine
xyplot(log(data[,3])~data[,2]|data[,1],panel=function(x,y){panel.xyplot(x,y)+panel.abline(coef(lm(y~x)))})
and I get perfect linear regression of my points
...But I would prefer to plot the exponential curves (y=exp ( a*x + b ))..
I tried the following formula :
>
xyplot(data[,3]~data[,2]|data[,1],panel=function(x,y){panel.xyplot(x,y)+panel.curve(coef(lm(log(y)~x))[1])})
and I get :
Error in model.frame(formula, rownames, variables, varnames, extras,
extranames, :
variable lengths differ (found for 'x')
... I don't really now what goes wrong and how to correct that
Maybe I am wrong in the use of the pannel.curve function ....
Do anyone know something about that ?
Thanks by advance
Jessica Gervais
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