[R-sig-ME] Weighted regression in REML
Nik Tuzov
m@n@pend @ending from ntuzov@com
Wed Oct 17 19:23:39 CEST 2018
Hello Ben:
Thanks for replying.
Unfortunately, it's hard for me or anyone else to determine when the copyright is violated. For instance, "The elements of statistical learning" is available on Amazon for a hefty price of $63, and yet the authors made the pdf freely available as well. I assumed that the same was true for Searle's book.
I have developed an implementation of Searle's algorithm based on the equations 96-99 and 91b. On top of that, it uses the multiplication trick to incorporate weights.It generates results that are close to those of PROC MIXED when there are no weights, or when weights are used w/o
random effects. However, when weights are used with random effects, the results are off. Did I get it right that, in your opinion, I should look for some error in the code?
Regards,Nik
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Today's Topics:
1. Dependency structure (Yashree Mehta)
2. Weighted regression in REML (Nik Tuzov)
3. Weighted regression in REML (Nik Tuzov)
4. Weighted regression in REML (Nik Tuzov)
5. Weighted regression in REML (Nik Tuzov)
6. Re: Weighted regression in REML (Ben Bolker)
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Message: 1
Date: Tue, 16 Oct 2018 19:03:27 +0200
From: Yashree Mehta <yashree19 using gmail.com>
To: r-sig-mixed-models using r-project.org
Subject: [R-sig-ME] Dependency structure
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Hi,
Is there literature on how to specify the dependency structure between the
random intercept and the statistical noise error term in a random intercept
model?
It would be useful to also know how to implement using R...
Thank you
Yashree
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Message: 2
Date: Tue, 16 Oct 2018 21:14:56 +0000 (UTC)
From: Nik Tuzov <manspend using ntuzov.com>
To: "r-sig-mixed-models using r-project.org"
<r-sig-mixed-models using r-project.org>
Subject: [R-sig-ME] Weighted regression in REML
Message-ID: <1070079121.11021335.1539724496863 using mail.yahoo.com>
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Hello:
I'm reading the book of Searle:
http://www.leg.ufpr.br/~eder/Variance%20Components.pdf
I think that equation 53 on p 276 suggests that if one wants to use weights in REML, the solution is very similar to that in OLS: multiply X, Z, and Y by the square root of the weight matrixand proceed as in unweighted case. Am I right or there is more that needs to be done?
Regards,Nik
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Message: 3
Date: Tue, 16 Oct 2018 21:17:39 +0000 (UTC)
From: Nik Tuzov <manspend using ntuzov.com>
To: "r-sig-mixed-models using r-project.org"
<r-sig-mixed-models using r-project.org>
Subject: [R-sig-ME] Weighted regression in REML
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Hello:
I'm reading the book of Searle:
http://www.leg.ufpr.br/~eder/Variance%20Components.pdf
I think that equation 53 on p 276 suggests that if one wants to use weights in REML, the solution is very similar to that in OLS: multiply X, Z, and Y by the square root of the weight matrixand proceed as in unweighted case. Am I right or there is more that needs to be done?
Regards,Nik
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Message: 4
Date: Tue, 16 Oct 2018 21:16:07 +0000 (UTC)
From: Nik Tuzov <manspend using ntuzov.com>
To: "r-sig-mixed-models using r-project.org"
<r-sig-mixed-models using r-project.org>
Subject: [R-sig-ME] Weighted regression in REML
Message-ID: <1606529909.11061754.1539724568007 using mail.yahoo.com>
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Hello:
I'm reading the book of Searle:
http://www.leg.ufpr.br/~eder/Variance%20Components.pdf
I think that equation 53 on p 276 suggests that if one wants to use weights in REML, the solution is very similar to that in OLS: multiply X, Z, and Y by the square root of the weight matrixand proceed as in unweighted case. Am I right or there is more that needs to be done?
Regards,Nik
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Message: 5
Date: Tue, 16 Oct 2018 21:21:48 +0000 (UTC)
From: Nik Tuzov <manspend using ntuzov.com>
To: "r-sig-mixed-models using r-project.org"
<r-sig-mixed-models using r-project.org>
Subject: [R-sig-ME] Weighted regression in REML
Message-ID: <1435233226.11048314.1539724908472 using mail.yahoo.com>
Content-Type: text/plain; charset="utf-8"
Hello:
I'mreading the book of Searle:
http://www.leg.ufpr.br/~eder/Variance%20Components.pdf
Ithink that equation 53 on p 276 suggests that if one wants to useweights in REML, the solution is very similar to that in OLS:multiply X, Z, and Y by the square root of the weight matrix andproceed as in unweighted case. Am I right or there is more that needsto be done?
Regards, Nik
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Message: 6
Date: Tue, 16 Oct 2018 20:27:36 -0400
From: Ben Bolker <bbolker using gmail.com>
To: r-sig-mixed-models using r-project.org
Subject: Re: [R-sig-ME] Weighted regression in REML
Message-ID: <a483cb3b-b15a-d30f-b7b2-65e97c2bef20 using gmail.com>
Content-Type: text/plain; charset="utf-8"
Can I please request that in general people **not** use this list to
post links to material that is (presumably) violating the
authors'/publisher's wishes? (A screenshot of a particular equation
would seem to constitute "fair use" ...)
FWIW your statement sounds correct to me -- in the Bates et al.
JSS/lmer paper (available via vignette("lmer", package="lme4")), the
development of the estimation procedure mostly leaves the weights out
for simplicity, but says:
"To allow for case weights, we save the products X^⊤ W X, X^⊤ W y, Z^⊤ W
X, Z^⊤ W y and Z^⊤ W Z (see Table 6)."
W is the weight matrix, so this is equivalent to multiplying X, y, Z
by W^(1/2) ...
cheers
Ben Bolker
On 2018-10-16 05:16 PM, Nik Tuzov wrote:
> Hello:
> I'm reading the book of Searle:
> http://www.leg.ufpr.br/~eder/Variance%20Components.pdf
>
> I think that equation 53 on p 276 suggests that if one wants to use weights in REML, the solution is very similar to that in OLS: multiply X, Z, and Y by the square root of the weight matrixand proceed as in unweighted case. Am I right or there is more that needs to be done?
> Regards,Nik
>
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>
> _______________________________________________
> R-sig-mixed-models using r-project.org mailing list
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