Hi: I don't think my paper applies because it needs the same y. Also, I don't think I follow what you're doing now ( now you have different y and different x's ? ) so I'd rather not comment but hopefully someone else does understand Good luck.
On Fri, Jan 27, 2012 at 4:10 PM, Michael <comtech....@gmail.com> wrote: > I changed the notation for data from x to z... > > That's it. Should be very clear now... Thanks! > > Data: z1, z2, ..., z_{n+1} > > y1 = z_1,z_2,......... z_n > y2 = z_2, z_3,......... z_{n+1} > > x1 = 1, ..., n > x2 = 1, ..., n > > y1 = A1+ x1 * B1 + epsilon_1 > y2 = A2 + x2 * B2 + epsilon_2 > > H0: B1 and B2 are statistically significally different... > > > > On Fri, Jan 27, 2012 at 2:41 PM, Mark Leeds <marklee...@gmail.com> wrote: > >> now i'm confused because you first use y_1, y_2 and then use y later. I >> would take >> a look at that earlier paper i mentioned. I think it's along the lines of >> what you want. Unfortunately. I don't have a computer copy of it. I got it >> from a library service where I once worked. >> >> >> mark >> >> >> On Fri, Jan 27, 2012 at 3:35 PM, Michael <comtech....@gmail.com> wrote: >> >>> Thanks all. >>> >>> Here are a more clear statement of my question: >>> >>> Data: z1, z2, ..., z_{n+1} >>> >>> y1 = z_1,z_2,......... z_n >>> y2 = z_2, z_3,......... z_{n+1} >>> >>> x1 = 1, ..., n >>> x2 = 1, ..., n >>> >>> y = A1+ x1 * B1 + epsilon_1 >>> y = A2 + x2 * B2 + epsilon_2 >>> >>> H0: B1 and B2 are statistically significally different... >>> >>> Any more thoughts? >>> >>> Thanks a lot! >>> >>> On Fri, Jan 27, 2012 at 1:39 PM, Mark Leeds <marklee...@gmail.com>wrote: >>> >>>> Hi Richard: I read michael's question as meaning that he says two >>>> univariate no intercept >>>> regression model where the predictor data is different in each model so >>>> that >>>> >>>> x1 = x_11,x_12,......... x_1n >>>> x2 = x_21, x_22,......... x_2n >>>> y = y_1, .....y_n >>>> >>>> y = x1 * B1 + epsilon_1 >>>> y = x2 * B2 + epsilon_2 >>>> >>>> and he wants to see which coefficient ( B1 or B2 ) "works" better. But >>>> I could be wrong >>>> which I only realized after reading your recommendation. michael: if >>>> i'm wrong, then disregard the paper reference that I sent earlier. >>>> >>>> >>>> Mark >>>> >>>> >>>> >>>> On Fri, Jan 27, 2012 at 2:29 PM, Richard M. Heiberger <r...@temple.edu >>>> > wrote: >>>> >>>>> It looks like you might be asking for the anova() on two models. >>>>> >>>>> M1 <- lm(y ~ x1 + x2 + x3, data=something) >>>>> M2 <- lm(y ~ x2 + x3, data=something) >>>>> anova(M1, M2) >>>>> >>>>> Please send a reproducible example to the list if more detail is >>>>> needed. >>>>> >>>>> Rich >>>>> >>>>> On Thu, Jan 26, 2012 at 11:59 PM, Michael <comtech....@gmail.com> >>>>> wrote: >>>>> >>>>> > Hi al, >>>>> > >>>>> > I am looking for a R command to test the difference of two linear >>>>> > regressoon betas. >>>>> > >>>>> > Lets say I have data x1, x2...x(nï¼1). >>>>> > beta1 is obtained from regressing x1 to xn onto 1 to n. >>>>> > >>>>> > beta2 is obtained from regressing x2 to x(nï¼1) onto 1 to n. >>>>> > >>>>> > Is there a way in R to test whether beta1 and beta2 are statistically >>>>> > different? >>>>> > >>>>> > Thanks a lot! >>>>> > >>>>> > [[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<http://www.r-project.org/posting-guide.html> >>>>> <http://www.r-project.org/posting-guide.html> >>>>> >>>>> > and provide commented, minimal, self-contained, reproducible code. >>>>> > >>>>> > >>>>> >>>>> [[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<http://www.r-project.org/posting-guide.html> >>>>> and provide commented, minimal, self-contained, reproducible code. >>>>> >>>>> >>>> >>> >> > [[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.