Thank you Peter, works perfectly.
Funny how simple things are once someone tells you the answer =)
robbie
On Tue, May 22, 2012 at 9:37 PM, Peter Ehlers wrote:
> Robbie,
>
> Here's what I *think* you are trying to do:
>
> 1.
> y is a cubic function of x:
>
> y = b1*x + b2*x^2 + b3*x^3
>
> 2.
Robbie,
Here's what I *think* you are trying to do:
1.
y is a cubic function of x:
y = b1*x + b2*x^2 + b3*x^3
2.
s is the cumsum of y:
s_i = y_1 + ... + y_i
3.
Given a subset of x = 1:n and the corresponding
values of s, estimate the coefficients of the cubic.
If that is the correct und
Ahh sorry -- I didn't understand that x was supposed to be an
index so I was using the row number an index for the summation -- yes,
my proposal probably won't work without further assumptions[I.e.,
you could assume linear growth between observations, but that will
bias something some direc
I don't think I can.
For the sample data
d <- data.frame(x=c(1, 4, 9, 12), s=c(109, 1200, 5325, 8216))
when x = 4, s = 1200. However, that s4 is sum of y1 + y2 + y3 + y4.
Wouldn't I have to know the y for x = 2 and x = 3 to get the value of y
for x = 4?
In the previous message, I created two
But if I understand your problem correctly, you can get the y values
from the s values. I'm relying on your statement that "s is sum of the
current y and all previous y (s3 = y1 + y2 + y3)." E.g.,
y <- c(1, 4, 6, 9, 3, 7)
s1 = 1
s2 = 4 + s1 = 5
s3 = 6 + s2 = 11
more generally
s <- cumsum(y)
Th
Hi all,
Thanks for the replies, but I realize I've done a bad job explaining my
problem. To help, I've created some sample data to explain the problem.
df <- data.frame(x=c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12), y=c(109, 232,
363, 496, 625, 744, 847, 928, 981, 1000, 979, 912), s=c(109, 341, 704
On May 18, 2012, at 1:44 PM, Robbie Edwards wrote:
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.
cumsum( rowSums( cbind(B1 * x, B2 * x^2, B3 * x^3)))
Anyway, if it wasn't for
Following up on Rolf's post:
1) cumulative summation (cumsum) maybe?
2) In fact, you should probably **not** fit the non-summation version
as you have stated. See ?poly.
I would guess that context is important here. Based on (my
interpretation) of the rather strange nature of your request, I
sus
On 19/05/12 05:44, Robbie Edwards wrote:
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)
Whe
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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