Polynomial fits : Run a set of polynomial mode (order 1-4) on some x vs y data.

polynomial_fits.R

#Run a set of polynomial models on some x vs y data. 

#create a data set x and y
x<-1:1100
y<-sqrt(x^6+x/x^4)+x/x^x

#Define function to run models
polyfit<-function(x,order,raw=TRUE)
{
  fit<-lm(y~poly(x,order,raw=raw))
  return (fit)}



#Fit first order model
fit1  <- polyfit(x = x,order = 1)
summary(fit1)

#second degree
fit2 <- polyfit(x = x,order = 2)
summary(fit2)
#third degree
fit3 <- polyfit(x = x,order = 3)
summary(fit3)
#fourth degree
fit4 <- polyfit(x = x,order = 4)
summary(fit4)

#simulate some new data
xx <- seq(min(x)-10,max(x)+10, length=500)

#plot real data
plot(x,y,pch=19,log="",cex=0.2)

#add lines for data predicted 
lines(xx, predict(fit1, data.frame(x=xx)), col="red")
lines(xx, predict(fit2, data.frame(x=xx)), col="blue")
lines(xx, predict(fit3, data.frame(x=xx)), col="green")
lines(xx, predict(fit4, data.frame(x=xx)), col="pink")