Automatic curve fitting in R

Question

Is there any package that automatically fits a curve using many simple models?
By simple models I mean:

• ax+b
• ax^2+bx+c
• a*log(x) + b

Answer 1

You can fit a Regression Splines and find a good fit by manually adjusting the degrees of freedom a few times. Try the following function:

spline.fit <- function(x, y, df=5) {
  ## INPUT: x, y are two vectors (predictor and response);
  ##        df is the number of spline basis.  Increase "df" to fit more adaptively to the data.
  require(splines) # available as default R Package.
  bx <- bs(x, df)  # B-spline basis matrix as New Predictors (dimension is "length(x)" by "df")
  f <- lm(y ~ bx)  # Linear Regression on Spline Basis (that is, "df" number of new predictors)
  fy <- fitted(f)  # Fitted Response
  plot(x, y); lines(x, fy, col="blue", lwd=2) # Make a plot to show the fit.
  invisible(list(x=bx, y=fy, f=f))    # Return the Basis (new predictors), Fitted Y, Regression
}

if (F) {                                # Unit Test
  spline.fit(1:100, rnorm(100))
  spline.fit(1:100, rnorm(100), df=20)
}