Difference between gam() and loess().

It seems that in general

	gam(y~lo(x)) # gam() from the gam package.

and
	loess(y~x)

give slightly different results (in respect of the predicted/fitted  
values).
Most noticeable at the endpoints of the range of x.

Can anyone enlighten me about the reason for this difference?

Is it possible to twiddle the control parameters, for either or both  
functions,
so as to obtain identical results?

Thanks.

	cheers,

		Rolf Turner

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