Re: [R] forecasting with non-linear models

Hi: You're fitting y as a function of x; as in any regression model, the x's are assumed to be conditionally fixed. If you want to model x as a function of y, that's a calibration problem. There are several issues at play: 1. In the model, you have assumed x is fixed, but afterward, you want to

Re: [R] forecasting with non-linear models

predict x for a given y(response)? If this is the case, you will have multiple x for a single y for this exponential model. In terms of logistic regression, If y =1, logit([P(Y=1)] = a + b*bx has infinite many x. The question seems not quite clear to me. -- View this message in context: http://

[R] forecasting with non-linear models

Dear colleagues! Is it possible to make predictions in R? there is an exponential relationship detween y and x x<-c(0.001,0.003,0.01,0.16,0.3,0.7,0.9) y<-c(38.8,41.5,44.2,27,26.9,6.9,3) f<-function(x,a,b){a*exp(b*x)} fm<-nls(y~f(x,a,b), start=c(a=1,b=1)) How one can predict x when y=10 and is it

[R] forecasting with non-linear models

Dear colleagues! Is it possible to make predictions in R? there is an exponential relationship detween y and x x<-c(0.001,0.003,0.01,0.16,0.3,0.7,0.9) y<-c(38.8,41.5,44.2,27,26.9,6.9,3) f<-function(x,a,b){a*exp(b*x)} fm<-nls(y~f(x,a,b), start=c(a=1,b=1)) How one can predict x when y=10 and is it