Fit polynomial in Excel with BERT/R.

poly.R

#
# fit a polynomial.  pass a range of x (independent), 
# y (dependent), and degree.
#
# returns a row vector by default, but pass False as 
# the last parameter and it will return a column vector.
#
fit.poly <- function( x, y, degree, as.row=T ){

	x <- unlist(as.numeric(x));
	y <- unlist(as.numeric(y));

	model <- lm( y ~ poly(x, degree=degree, raw=T ));
	
	if( as.row ){ 
		matrix( model$coefficients, nrow=1 ); 
	}
	else {
		model$coefficients;
	}

}


#
# fit a polynomial using normal equation
#
fit.poly.ne <- function( x, y, degree, as.row=T ){

	x <- unlist(as.numeric(x));
	y <- unlist(as.numeric(y));

	X <- sapply( 0:degree, function(p){ x^p; })	
	coeff <- solve( t(X) %*% X ) %*% t(X) %*% y;

	if( as.row ){ matrix( coeff, nrow=1 ); }
	else { coeff; }

}