z1 <- cumsum(x)})
>
> coef(lm(s ~ 0 + z1 + z2 + z3, data = e))
>
> # z1 z2 z3
> # 100 10 -1
>
>
> Peter Ehlers
>
>
> On 2012-05-22 09:43, Robbie Edwards wrote:
>
>> I don't think I can.
>>
>> For the sample data
>>
>> d
3 = 6 + s2 = 11
>
> more generally
>
> s <- cumsum(y)
>
> Then if we only see s, we can get back the y vector by doing
>
> c(s[1], diff(s))
>
> which is identical to y.
>
> So for your data, the underlying y must have been c(109, 1091, 4125,
> 2891) rig
d to use a few sample points to help define the parameters of
the curve.
thanks again and hopefully this makes the problem a bit clearer.
robbie
On Fri, May 18, 2012 at 7:40 PM, David Winsemius wrote:
>
> On May 18, 2012, at 1:44 PM, Robbie Edwards wrote:
>
> Hi all,
>>
>&
Hi all,
I'm trying to model some data where the y is defined by
y = summation[1 to 50] B1 * x + B2 * x^2 + B3 * x^3
Hopefully that reads clearly for email.
Anyway, if it wasn't for the summation, I know I would do it like this
lm(y ~ x + x2 + x3)
Where x2 and x3 are x^2 and x^3.
However, sin
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