Re: [R] Question on partial effect

2006-07-11 Thread Guo Wei-Wei
Than you, Gavin. You helped me out a lot of problems.

Thank you very much!
Wei-Wei




2006/7/12, Gavin Simpson <[EMAIL PROTECTED]>:
> On Wed, 2006-07-12 at 00:51 +0800, Guo Wei-Wei wrote:
> > Thank you, Gavin. I think that might be what I need. But I'm a little
> > bit wandering what's the scale of resid(mod). Is it
> > scale(dist)/scale(speed), for example kilometer / (kilometer per
> > hour)? or something else?
> >
> > Thank you very much!
> > Wei-Wei
>
> The scale of dist - they are just the differences between observed dist
> and fitted dist (based on speed).
>
> mod <- lm(dist ~ speed, data = cars)
> resid(mod)
>
>  1  2  3  4  5
>   3.849460  11.849460  -5.947766  12.052234   2.119825
>  6  7  8  9 10
>  -7.812584  -3.744993   4.255007  12.255007  -8.677401
> 
>
> # visualise the residuals
> plot(resid(mod) ~ dist, data = cars)
> abline(h = 0, col = "grey")
> ## length of blue line represents the residual
> lines(cars$dist, resid(mod), type = "h", col = "blue")
>
> So you see that for the 1st residual it is 3.849 ft (the distances are
> measured in feet, see ?cars)
>
> Does this help?
>
> G
>
> >
> >
> > 2006/7/12, Gavin Simpson <[EMAIL PROTECTED]>:
> > > On Tue, 2006-07-11 at 23:51 +0800, Guo Wei-Wei wrote:
> > > > Dear all,
> > > >
> > > > I don't know what's my question is called. I have a performance
> > > > variable A, such as sales. And I have another variable B, let's say
> > > > establish time of firm. I want to create the third variable that is
> > > > sales without the effect of establish time. Maybe it can be called
> > > > partial effect problem. I'm not sure.
> > > >
> > > > Does anyone have any suggestion? Thank you in advance!
> > > >
> > > > All the best,
> > > > Wei-Wei
> > >
> > > Do you mean?
> > >
> > > ## dummy data
> > > A <- rnorm(100)
> > > B <- rnorm(100)
> > > C <- resid(lm(A ~ B))
> > >
> > > C now contains the residual variation in A after fitting B.
> > >
> > > e.g. with some real data
> > > ?cars
> > > data(cars) # not sure this is needed now, I forget
> > > mod <- lm(dist ~ speed, data  = cars)
> > > summary(mod)
> > > partial <- resid(mod)
> > >
> > > ## check
> > > mod2 <- lm(dist ~ partial, data = cars)
> > > summary(mod2)
> > > ## from the two R^2 form mod1 and mod2 - partial contains dist minus
> > > ## the effects of speed
> > > > 0.6511 + 0.3489
> > > [1] 1
> > >
> > > HTH
> > >
> > > G
> > > --
> > > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
> > >  Gavin Simpson [t] +44 (0)20 7679 0522
> > >  ECRC & ENSIS, UCL Geography,  [f] +44 (0)20 7679 0565
> > >  Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
> > >  Gower Street, London  [w] http://www.ucl.ac.uk/~ucfagls/cv/
> > >  London, UK. WC1E 6BT. [w] http://www.ucl.ac.uk/~ucfagls/
> > > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
> > >
> > >
> >
> > __
> > [email protected] mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide! 
> > http://www.R-project.org/posting-guide.html
> --
> %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
>  Gavin Simpson [t] +44 (0)20 7679 0522
>  ECRC & ENSIS, UCL Geography,  [f] +44 (0)20 7679 0565
>  Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
>  Gower Street, London  [w] http://www.ucl.ac.uk/~ucfagls/cv/
>  London, UK. WC1E 6BT. [w] http://www.ucl.ac.uk/~ucfagls/
> %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
>
>

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Re: [R] Question on partial effect

2006-07-11 Thread Gavin Simpson
On Wed, 2006-07-12 at 00:51 +0800, Guo Wei-Wei wrote:
> Thank you, Gavin. I think that might be what I need. But I'm a little
> bit wandering what's the scale of resid(mod). Is it
> scale(dist)/scale(speed), for example kilometer / (kilometer per
> hour)? or something else?
> 
> Thank you very much!
> Wei-Wei

The scale of dist - they are just the differences between observed dist
and fitted dist (based on speed). 

mod <- lm(dist ~ speed, data = cars)
resid(mod)

 1  2  3  4  5
  3.849460  11.849460  -5.947766  12.052234   2.119825
 6  7  8  9 10
 -7.812584  -3.744993   4.255007  12.255007  -8.677401


# visualise the residuals
plot(resid(mod) ~ dist, data = cars)
abline(h = 0, col = "grey")
## length of blue line represents the residual
lines(cars$dist, resid(mod), type = "h", col = "blue")

So you see that for the 1st residual it is 3.849 ft (the distances are
measured in feet, see ?cars)

Does this help?

G

> 
> 
> 2006/7/12, Gavin Simpson <[EMAIL PROTECTED]>:
> > On Tue, 2006-07-11 at 23:51 +0800, Guo Wei-Wei wrote:
> > > Dear all,
> > >
> > > I don't know what's my question is called. I have a performance
> > > variable A, such as sales. And I have another variable B, let's say
> > > establish time of firm. I want to create the third variable that is
> > > sales without the effect of establish time. Maybe it can be called
> > > partial effect problem. I'm not sure.
> > >
> > > Does anyone have any suggestion? Thank you in advance!
> > >
> > > All the best,
> > > Wei-Wei
> >
> > Do you mean?
> >
> > ## dummy data
> > A <- rnorm(100)
> > B <- rnorm(100)
> > C <- resid(lm(A ~ B))
> >
> > C now contains the residual variation in A after fitting B.
> >
> > e.g. with some real data
> > ?cars
> > data(cars) # not sure this is needed now, I forget
> > mod <- lm(dist ~ speed, data  = cars)
> > summary(mod)
> > partial <- resid(mod)
> >
> > ## check
> > mod2 <- lm(dist ~ partial, data = cars)
> > summary(mod2)
> > ## from the two R^2 form mod1 and mod2 - partial contains dist minus
> > ## the effects of speed
> > > 0.6511 + 0.3489
> > [1] 1
> >
> > HTH
> >
> > G
> > --
> > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
> >  Gavin Simpson [t] +44 (0)20 7679 0522
> >  ECRC & ENSIS, UCL Geography,  [f] +44 (0)20 7679 0565
> >  Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
> >  Gower Street, London  [w] http://www.ucl.ac.uk/~ucfagls/cv/
> >  London, UK. WC1E 6BT. [w] http://www.ucl.ac.uk/~ucfagls/
> > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
> >
> >
> 
> __
> [email protected] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
-- 
%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
 Gavin Simpson [t] +44 (0)20 7679 0522
 ECRC & ENSIS, UCL Geography,  [f] +44 (0)20 7679 0565
 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
 Gower Street, London  [w] http://www.ucl.ac.uk/~ucfagls/cv/
 London, UK. WC1E 6BT. [w] http://www.ucl.ac.uk/~ucfagls/
%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%

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Re: [R] Question on partial effect

2006-07-11 Thread Guo Wei-Wei
Thank you, Gavin. I think that might be what I need. But I'm a little
bit wandering what's the scale of resid(mod). Is it
scale(dist)/scale(speed), for example kilometer / (kilometer per
hour)? or something else?

Thank you very much!
Wei-Wei


2006/7/12, Gavin Simpson <[EMAIL PROTECTED]>:
> On Tue, 2006-07-11 at 23:51 +0800, Guo Wei-Wei wrote:
> > Dear all,
> >
> > I don't know what's my question is called. I have a performance
> > variable A, such as sales. And I have another variable B, let's say
> > establish time of firm. I want to create the third variable that is
> > sales without the effect of establish time. Maybe it can be called
> > partial effect problem. I'm not sure.
> >
> > Does anyone have any suggestion? Thank you in advance!
> >
> > All the best,
> > Wei-Wei
>
> Do you mean?
>
> ## dummy data
> A <- rnorm(100)
> B <- rnorm(100)
> C <- resid(lm(A ~ B))
>
> C now contains the residual variation in A after fitting B.
>
> e.g. with some real data
> ?cars
> data(cars) # not sure this is needed now, I forget
> mod <- lm(dist ~ speed, data  = cars)
> summary(mod)
> partial <- resid(mod)
>
> ## check
> mod2 <- lm(dist ~ partial, data = cars)
> summary(mod2)
> ## from the two R^2 form mod1 and mod2 - partial contains dist minus
> ## the effects of speed
> > 0.6511 + 0.3489
> [1] 1
>
> HTH
>
> G
> --
> %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
>  Gavin Simpson [t] +44 (0)20 7679 0522
>  ECRC & ENSIS, UCL Geography,  [f] +44 (0)20 7679 0565
>  Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
>  Gower Street, London  [w] http://www.ucl.ac.uk/~ucfagls/cv/
>  London, UK. WC1E 6BT. [w] http://www.ucl.ac.uk/~ucfagls/
> %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
>
>

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Re: [R] Question on partial effect

2006-07-11 Thread Gavin Simpson
On Tue, 2006-07-11 at 23:51 +0800, Guo Wei-Wei wrote:
> Dear all,
> 
> I don't know what's my question is called. I have a performance
> variable A, such as sales. And I have another variable B, let's say
> establish time of firm. I want to create the third variable that is
> sales without the effect of establish time. Maybe it can be called
> partial effect problem. I'm not sure.
> 
> Does anyone have any suggestion? Thank you in advance!
> 
> All the best,
> Wei-Wei

Do you mean?

## dummy data
A <- rnorm(100)
B <- rnorm(100)
C <- resid(lm(A ~ B))

C now contains the residual variation in A after fitting B.

e.g. with some real data
?cars
data(cars) # not sure this is needed now, I forget
mod <- lm(dist ~ speed, data  = cars)
summary(mod)
partial <- resid(mod)

## check
mod2 <- lm(dist ~ partial, data = cars)
summary(mod2)
## from the two R^2 form mod1 and mod2 - partial contains dist minus
## the effects of speed
> 0.6511 + 0.3489
[1] 1

HTH

G
-- 
%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
 Gavin Simpson [t] +44 (0)20 7679 0522
 ECRC & ENSIS, UCL Geography,  [f] +44 (0)20 7679 0565
 Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
 Gower Street, London  [w] http://www.ucl.ac.uk/~ucfagls/cv/
 London, UK. WC1E 6BT. [w] http://www.ucl.ac.uk/~ucfagls/
%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%

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[R] Question on partial effect

2006-07-11 Thread Guo Wei-Wei
Dear all,

I don't know what's my question is called. I have a performance
variable A, such as sales. And I have another variable B, let's say
establish time of firm. I want to create the third variable that is
sales without the effect of establish time. Maybe it can be called
partial effect problem. I'm not sure.

Does anyone have any suggestion? Thank you in advance!

All the best,
Wei-Wei

__
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html