RBaskin@ahrq.gov
2003-Oct-30 19:49 UTC
[R] Variance of a non-linear combination of the coefficient e stiamtes
< In Stata, I can just use "bs" function ...>
in STATA the bs command runs a bootstrap
If you want to use the bootstrap function (or you could linearize b*c/a :)
look under ?boot (you may need to load the package first).
Usage:
boot(data, statistic, R, sim="ordinary", stype="i",
strata=rep(1,n), L=NULL, m=0, weights=NULL,
ran.gen=function(d, p) d, mle=NULL, ...)
I tried to provide an example - others can clean up the R code for me:
> test.df<-cbind(rnorm(25),rnorm(25),rnorm(25))
> test.model<-lm(test.df[,1]~test.df[,2]+test.df[,3])
> summary(test.model)
Call:
lm(formula = test.df[, 1] ~ test.df[, 2] + test.df[, 3])
Residuals:
Min 1Q Median 3Q Max
-1.3784 -0.6903 -0.2278 0.5879 2.7298
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.03419 0.20907 -0.164 0.872
test.df[, 2] -0.29636 0.17705 -1.674 0.108
test.df[, 3] 0.16059 0.21060 0.763 0.454
Residual standard error: 1.018 on 22 degrees of freedom
Multiple R-Squared: 0.1439, Adjusted R-squared: 0.06613
F-statistic: 1.85 on 2 and 22 DF, p-value: 0.1809
>
test.model$coefficients[2]*test.model$coefficients[3]/test.model$coefficient
s[1]
test.df[, 2]
1.391884 > umeno.stat<-function(xx,...){
+ xx.model<-lm(xx[...,1]~xx[...,2]+xx[...,3])
+
xx.model$coefficient[2]*xx.model$coefficient[3]/xx.model$coefficient[1]}> umeno.stat(test.df,c(1:25))
xx[..., 2]
1.391884 > boot(test.df,umeno.stat,100)
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = test.df, statistic = umeno.stat, R = 100)
Bootstrap Statistics :
original bias std. error
t1* 1.391884 0.2708119 16.32276>
bob
-----Original Message-----
From: umeno [mailto:umeno@students.uiuc.edu]
Sent: Thursday, October 30, 2003 1:19 PM
To: R-Help <r-help
Subject: [R] Variance of a non-linear combination of the coefficient
estiamtes
Hi,
I would like to know if anyone knows how to compute a variance of the
non-linear combination of the coefficient estimates.
Say, I get a model of
y~c+ax+bz (1)
where x and z are the independent variables, c is the constant estimate, and
a
and b are the coefficient estimates.
Then, I want to know the variance of
b*c/a (2).
How am I going to get it?
In Stata, I can just use "bs" function by defining the regression
model (1)
and the statistic of the interest(2).
Help!!!
Thank you
Soyoko
______________________________________
Ms. Soyoko Umeno
Graduate Research Assitant for the Illinois-Missouri Biotechnology Alliance
(IMBA) at http://www.imba.missouri.edu/
Ph.D. Student at the Department of Agricultural and Consumer Economics
at the University of Illinois at Urbana-Champaign
Office Phone: 217-333-3417 or 217-333-0364
Fax: 217-244-4817
Mailing Address: 1301 W. Gregory Dr. MC710, Urbana, IL 61801
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