[R] Intersection for two curves

[David Winsemius]

On Apr 23, 2010, at 8:06 PM, Muhammad Rahiz wrote:

> Thanks David & Peter,
>
> The locator() works but not practical as I have to repeat the  
> process many times.
>
> Does the code works on linear regression only?

Should work for any process that can produce a function.

> When i tried to find the intersection at a non-linear curve, i get  
> the following error
> Error in optimize(f = function(x) abs(xyf(ds) - n), c(0, 13)) :
>  invalid function value in 'optimize'

Why did you did not change the name of the function?
And the code below would not have produced that error, so why did you  
post it?

>
> I'd like to know what the error means and how I can correct it.
>
> I have my sample data and code as follows;
>
>
> *   s1         cm
> 1    0 0.57223196
> 2   10 0.33110049
> 3   20 0.11163181
> 4   30 0.10242237
> 5   40 0.09254315
> 6   50 0.02739370
> 7   60 0.02567137
> 8   70 0.02492397
> 9   80 0.03206637
> 10  90 0.02487381
> 11 100 0.01747584
> 12 110 0.15977533
> 13 120 0.13317708
>
> rm(list=ls())

PLEASE, DON'T DO THAT!!!!. Or rather you can do it in your workspace  
but don't post it. It's not fair to a person who may not read your  
code line by line before pasting it into their workspace and having it  
wiped out. Do you expect us to completely clear out our workspaces  
just so we can answer your questions? At the very least comment it out  
so it doesn't blow away half a days work for someone who is trying to  
be helpful.

> x<- read.table("test.data.txt",header=TRUE)
>
> ds <- x[,2] # distance
> cr <- x[,3] # correlation values
> plot(ds,cr)
> n <- 1/2.71
> abline(h=n)
>
> fc <- function(x,a,b){a*exp(-b*x)}    # where a & b are constants
> fm <- nls(cr ~ fc(ds,a,b),start=c(a=1,b=0))
> co <- coef(fm)

> curve(fc(x,a=co[1],b=co[2]),add=TRUE,col="red",lwd=1.5)
>
> int <- function(x) coef(fm)[1] + x*coef(fm)[2]
> in1 <- optimize(f=function(x) c(0,120), abs(int(ds)-n))

Huh? I don't really see anything in there that would be a function. I  
think you would need to specify "fc" and coefficient values for "a"  
and "b".

> abline(v=in1$minimize)   # ????

I think you would use in1$minimum once you get this far.

>
> thanks,
> Muhammad
>
>
>
>
> On 04/23/2010 07:32 PM, Peter Ehlers wrote:
>> On 2010-04-23 11:46, David Winsemius wrote:
>>
>>> On Apr 23, 2010, at 1:06 PM, Muhammad Rahiz wrote:
>>>
>>>
>>>> Does anyone know of a method that I can get the intersection  
>>>> where the
>>>> red and blue curves meet i.e. the value on the x-axis?
>>>>
>>>> x<- 1:10
>>>> y<- 10:1
>>>> plot(x,y)
>>>> abline(lm(y~x),col="blue")
>>>> abline(h=2.5,col="red")
>>>>
>>> Two ways :
>>>
>>>  >  xy<- lm(y~x)
>>>  >  xyf<- function(x) coef(xy)[1] +x*coef(xy)[2]
>>>
>>> # absolute difference
>>>  >  optimise(f=function(x) abs(xyf(x)-2.5), c(1,10) )
>>> $minimum
>>> [1] 8.49998
>>>
>>> $objective
>>> (Intercept)
>>> 1.932015e-05
>>>
>>> #N minimize squared difference
>>>  >  optimise(f=function(x) (xyf(x)-2.5)^2, c(1,10) )
>>> $minimum
>>> [1] 8.5
>>>
>>> $objective
>>> (Intercept)
>>> 3.155444e-30
>>>
>>>
>> Another (crude) way is to use locator(). I usually maximize
>> the plot window for this.
>>
>>

David Winsemius, MD
West Hartford, CT