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 <markleeds2@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.usa@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 <markleeds2@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 <rmh@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.usa@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(n＋1).
>>>> > beta1 is obtained from regressing x1 to xn onto 1 to n.
>>>> >
>>>> > beta2 is obtained from regressing x2 to x(n＋1) 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.
>>>>
>>>>
>>>
>>
>

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