[R] mgcv gam predict problem

[Simon Wood]

You can get around this by using the 'knots' argument to 'gam' to 
specify p-spline knots which span the range over which you want to 
predict. Alternatively use the "cr", "tp" or "ds" bases (splines with 
derivative based penalties), which don't have this problem.

best,
Simon

On 28/03/11 06:10, Philip Gautier wrote:
> Hello
>
> I'm using function gam from package mgcv to fit splines.  When I try
> to make a prediction slightly beyond the original 'x' range, I get
> this error:
>
>> A = runif(50,1,149)
>> B = sqrt(A) + rnorm(50)
>> range(A)
> [1]   3.289136 145.342961
>>
>>
>> fit1 = gam(B ~ s(A, bs="ps"), outer.ok=TRUE)
>> predict(fit1, newdata=data.frame(A=149.9), outer.ok=TRUE)
> Error in splineDesign(knots, x, ord, derivs, outer.ok = outer.ok) :
>    the 'x' data must be in the range 3.14708 to 145.485 unless you set
> 'outer.ok = TRUE'
>>
>
> I've inserted the argument 'outer.ok=TRUE' as you can see, but it
> hasn't helped.  How can I obtain this prediction?
>
> Thanks,
> Philip Gautier
> Dept. of Mathematics and Statistics
> American University, Washington, DC
>
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-- 
Simon Wood, Mathematical Science, University of Bath BA2 7AY UK
+44 (0)1225 386603               http://people.bath.ac.uk/sw283