[R] picewise function in nls....

[akshay kulkarni]

dear members,
                            I have two predictors, x1 and x2, and one response variable, y. Moreover, a step function models the relationship between y and x1:

fx <-   (x1 <= -2)*(x1^2) + (x1 > -2 && x1 < 2)*(x1^3) + (x1 > = 2)*(x1^4)

Can I include fx in an nls call  to create something like this:

NLS1 <- nls(y ~ a*(sin(x2) + fx), start = list(a = 2))   ?

Will the above work? Or should I do something like this:

if(x1 <= -2) {

NLS2 <- nls(y[x1 <= -2] ~ a*(sin(x2[x1 <= -2]) + x1^2),start = list(a = 3))   }

if(x1 > -2 && x1 < 2)  {

NLS3 <- nls(y[x1 > -2 && x1 < 2] ~ a*(sin(x2[x1  > -2 && x1 < 2]) + x1^3),start = list(a = 4))   }

if(x1 > = 2) {

NLS4 <- nls(y[x1 >= 2] ~ a*(sin(x2[x1 >= 2]) + x1^4),start = list(a = 5))   }


If the first case doesn't work, is there any other method to include the step function in the nls call without resorting to the if statements?

Also, the coefficient, a , gotten from the above two cases are different. Will this affect the precision of the nonlinear fir between
y ~ (f(x1),f(x2)) ?


very many thanks for your time and effort
yours sincerely,

AKSHAY M KULKARNI

	[[alternative HTML version deleted]]