Re: [R] Constrained OLS regression
In addition to Dimitris's approach, probably the following is more
straightforward..(the idea is the same, but implementation is simpler;
you do not need starting values, for instance..)
Given the linear predictor lp:
b0+b1X1+b2X2
as b2=1-b1 the lp becomes:
b0+b1X1+(1-b1)X2 = b0+b1(X1-X2)+offset(X2)
Hence for a generic GLM you can type
glm(y~1+I(x1-x2)+offset(x2))
Hope this helps,
vito
Dimitris Rizopoulos wrote:
you could reparameterize, e.g.,
x1 - runif(100, -4, 4)
x2 - runif(100, -4, 4)
X - cbind(1, x1 , x2)
y - rnorm(100, as.vector(X %*% c(5, -3, 4)), 2)
##
fn - function(betas){
betas - c(betas, 1 - betas[2])
crossprod(y - X %*% betas)[1, ]
}
opt - optim(c(5, -3), fn, method = BFGS)
c(opt$par, 1 - opt$par[2])
I hope it helps.
Best,
Dimitris
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
- Original Message -
From: Mesomeris, Spyros [CIR] [EMAIL PROTECTED]
To: r-help@stat.math.ethz.ch
Sent: Wednesday, September 27, 2006 12:51 PM
Subject: [R] Constrained OLS regression
Hello R helpers,
I am trying to do a linear OLS regression of y on two variables x1
and
x2. I want to constrain the coefficients of x1 and x2 to sum up to
1.
and therefore run a constrained OLS. Can anybody help with this? (I
have
seen some answers to similar questions but it was not clear to me
what I
need to do) - I have tried the lm function with offset but I must
not
have used it properly.
Thanks,
Spyros
__
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--
Vito M.R. Muggeo
Dip.to Sc Statist e Matem `Vianelli'
Università di Palermo
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fax: 091 485726/485612
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] Constrained OLS regression
Hello R helpers, I am trying to do a linear OLS regression of y on two variables x1 and x2. I want to constrain the coefficients of x1 and x2 to sum up to 1. and therefore run a constrained OLS. Can anybody help with this? (I have seen some answers to similar questions but it was not clear to me what I need to do) - I have tried the lm function with offset but I must not have used it properly. Thanks, Spyros __ R-help@stat.math.ethz.ch 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.
Re: [R] Constrained OLS regression
Have a look at the linear.hypothesis function in the car package. For example: mod.duncan - lm(prestige ~ income + education, data=Duncan) linear.hypothesis(mod.duncan, income + education = 1) Linear hypothesis test Hypothesis: income + education = 1 Model 1: prestige ~ income + education Model 2: restricted model Res.DfRSS Df Sum of Sq F Pr(F) 1 42 7506.7 2 43 8045.2 -1-538.5 3.0129 0.08994 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 On 27/09/06, Mesomeris, Spyros [CIR] [EMAIL PROTECTED] wrote: Hello R helpers, I am trying to do a linear OLS regression of y on two variables x1 and x2. I want to constrain the coefficients of x1 and x2 to sum up to 1. and therefore run a constrained OLS. Can anybody help with this? (I have seen some answers to similar questions but it was not clear to me what I need to do) - I have tried the lm function with offset but I must not have used it properly. Thanks, Spyros __ R-help@stat.math.ethz.ch 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. -- = David Barron Said Business School University of Oxford Park End Street Oxford OX1 1HP __ R-help@stat.math.ethz.ch 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.
Re: [R] Constrained OLS regression
you could reparameterize, e.g.,
x1 - runif(100, -4, 4)
x2 - runif(100, -4, 4)
X - cbind(1, x1 , x2)
y - rnorm(100, as.vector(X %*% c(5, -3, 4)), 2)
##
fn - function(betas){
betas - c(betas, 1 - betas[2])
crossprod(y - X %*% betas)[1, ]
}
opt - optim(c(5, -3), fn, method = BFGS)
c(opt$par, 1 - opt$par[2])
I hope it helps.
Best,
Dimitris
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
- Original Message -
From: Mesomeris, Spyros [CIR] [EMAIL PROTECTED]
To: r-help@stat.math.ethz.ch
Sent: Wednesday, September 27, 2006 12:51 PM
Subject: [R] Constrained OLS regression
Hello R helpers,
I am trying to do a linear OLS regression of y on two variables x1
and
x2. I want to constrain the coefficients of x1 and x2 to sum up to
1.
and therefore run a constrained OLS. Can anybody help with this? (I
have
seen some answers to similar questions but it was not clear to me
what I
need to do) - I have tried the lm function with offset but I must
not
have used it properly.
Thanks,
Spyros
__
R-help@stat.math.ethz.ch 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.
Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm
__
R-help@stat.math.ethz.ch 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.
