als for these coefficients. Do anyone happen to know
it?
At 2016-05-05 03:55:45, "David Winsemius" wrote:
>
>> On May 4, 2016, at 7:45 AM, super wrote:
>>
>>
>> Dear experts,
>>I have a problem in compute Bonferroni,Tukey's,Sheffe 95%-condence
Dear experts,
I have a problem in compute Bonferroni,Tukey's,Sheffe 95%-condence intervals
for coefficients B1,B2,B3 in linear regression using R? how can i do it? I only
know how to compute these three cofindence intervals in multicomparsion by
using multcomp package, and i am search a lot
Hadley wickham is goting to teach a two day course on advanced R and package
development in NYC, Sep 8-9.
You can learn more in
https://www.eventbrite.com/e/master-r-developer-workshop-tickets-11846598495
Could students from NYC make a trial to recording the course if permitted?
[[a
I now have two win7s in a local area network called A and B.
A now can run shiny app, and it shows that it listen 192.168.1.100:6271. And A
can visite the app in A's own chrome using 192.168.1.100:6271.
Then I want to B to visite A's shiny app. I type 192.168.1.100:6271 in chrome,
but it doesn
redefine);.(oldbody);.(addstuff)},list(redefine=quote(return<-function(x){x}),oldbody=oldbody,addstuff=quote(function(){})))
body(f1)<-newbody
closure<-f1()
ls(environment(closure))
environment(closure)$f3
Is there a easy way to do my original task?
At 2014-07-27 09:41:49, "sup
<- body(f)
>> newBody <- bquote({ .(origBody) ; .(addedStuff) }, list(origBody=origBody,
>> addedStuff=quote(function(){})))
>> body(f) <- newBody
>> f
>function ()
>{
>{
>1
>}
>function() {
>}
>}
>> f()
>fu
Suppose that I had a function as below:
f<-function() {
return(1)
}
i want to change the body of f to the form like this:
f<-function(){
1
function() {}
}
How can i do the task using body(f) or something else solutions?
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actually
represent it's value? I hope you can read the section expressions.
At 2014-07-24 07:15:55, "Duncan Murdoch" wrote:
>On 24/07/2014, 2:41 AM, super wrote:
>> The question is as below:
>> Exercises
>> 1.The following two calls look the same, but are
The question is as below:
Exercises
1.The following two calls look the same, but are actually different:
(a <- call("mean", 1:10))
#> mean(1:10)
(b <- call("mean", quote(1:10)))
#> mean(1:10)
identical(a, b)
#> [1] FALSE
What¡¯s the difference? Which one should you prefer?
So, how i can figure ou
The question is as below:
Exercises
1.The following two calls look the same, but are actually different:
(a <- call("mean", 1:10))
#> mean(1:10)
(b <- call("mean", quote(1:10)))
#> mean(1:10)
identical(a, b)
#> [1] FALSE
What¡¯s the difference? Which one should you prefer?
So, how i can figure ou
Dear all,
I just can't figure out what is the group generic mean, I know s3 object
oriented system, and there is a generic function concept there, i know it, but
when come to the group generic, i can't understand, please help ...
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__
n Tue, 2010-06-22 at 23:11 -0700, cc super wrote:
> > Hi, everyone,
> >
> > Night. I have three questions about multiple linear regression in R.
> >
> > Q1:
> >
> > y=rnorm(10,mean=5)
> > x1=rnorm(10,mean=2)
> > x2=rnorm(10)
> > lin=lm(
Hi, everyone,
Night. I have three questions about multiple linear regression in R.
Q1:
y=rnorm(10,mean=5)
x1=rnorm(10,mean=2)
x2=rnorm(10)
lin=lm(y~x1+x2)
summary(lin)
## In the summary, 'Residual standard error: 1.017 on 7 degrees of freedom',
1.017 is the estimate of the constance variance?
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