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) 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) right? Or have I completely misunderstood your problem? Michael On Tue, May 22, 2012 at 12:25 PM, Robbie Edwards <robbie.edwa...@gmail.com> wrote: > Actually, I can't. I don't know the y values. Only the s and only for a > subset of the data. > > Like this. > > d <- data.frame(x=c(1, 4, 9, 12), s=c(109, 1200, 5325, 8216)) > > > > On Tue, May 22, 2012 at 11:57 AM, R. Michael Weylandt > <michael.weyla...@gmail.com> wrote: >> >> You can reconstruct the y values by taking first-differences of the s >> vector, no? Then it sounds like you're good to go >> >> Best, Michael >> >> On Tue, May 22, 2012 at 11:40 AM, Robbie Edwards >> <robbie.edwa...@gmail.com> wrote: >> > 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, >> > 1200, 1825, 2569, 3416, 4344, 5325, 6325, 7304, 8216)) >> > >> > In this data frame, y results from y = x * b1 + x^2 * b2 + x^3 * b3 and >> > s >> > is sum of the current y and all previous y (s3 = y1 + y2 + y3). >> > >> > I know I can find b1, b2 and b3 using: >> > lm(y ~ 0 + x + I(x^2) + I(x^3), data=df) >> > >> > yielding... >> > Coefficients: >> > x I(x^2) I(x^3) >> > 100 10 -1 >> > >> > However, I need to find b1, b2 and b3 using the s column. The reason >> > being, I don't actually know the values of y in the actual data set. >> > And >> > in the actual data, I only have a few of the values. Imagine this data >> > is >> > being used a reward schedule for like a loyalty points program. y >> > represents the number of points needed for each level while s is the >> > total >> > number of points to reach that level. In the real problem, my data >> > looks >> > more like this: >> > >> > d <- data.frame(x=c(1, 4, 9, 12), s=c(109, 1200, 5325, 8216)) >> > >> > Where I need 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 >> > <dwinsem...@comcast.net>wrote: >> > >> >> >> >> 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 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, since each value of x is related to the previous values of x, >> >>> I >> >>> don't know how to do this. Any help is greatly appreciated. >> >>> >> >>> >> >>> >> >> >> >> David Winsemius, MD >> >> West Hartford, CT >> >> >> >> >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help@r-project.org mailing list >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.