Re: [R] passing an extra argument to an S3 generic
On 2/11/2012 12:00 PM, ilai wrote:
You are setting a new class (inflmlm) at the end of mlm.influence.
Remove that second to last line and enjoy your new S3 method.
Thanks for the suggestion, but it doesn't help -- I still get the same
behavior whether mlm.influence returns a classed object or not.
As well, I am defining print.inflmlm() and as.data.frame.inflmlm()
methods for these objects, so I do need mlm.influence to return a
classed object.
My hatvalues.mlm is designed to be similar in structure to
stats::hatvalues.lm where the S3 generic is defined.
hatvalues.mlm - function(model, m=1, infl, ...)
{
if (missing(infl)) {
infl - mlm.influence(model, m=m, do.coef=FALSE);
}
hat - infl$H
m - infl$m
names(hat) - if(m==1) infl$subsets else apply(infl$subsets,1,
paste, collapse=',')
hat
}
hatvalues
function (model, ...)
UseMethod(hatvalues)
bytecode: 0x0326fd30
environment: namespace:stats
hatvalues.lm
function (model, infl = lm.influence(model, do.coef = FALSE),
...)
{
hat - infl$hat
names(hat) - names(infl$wt.res)
hat
}
bytecode: 0x0326de6c
environment: namespace:stats
The idea is that the infl= argument specifies a call to the
computational function, mlm.influence() in my case, just as
lm.influence() does in the stats package.
The logic of UseMethod is that it should dispatch on the class of the
*first* argument to the function, which in my test case is c(mlm, lm)
Rohwer.mod - lm(cbind(SAT, PPVT, Raven) ~ n+s+ns+na+ss, data=Rohwer2)
class(Rohwer.mod)
[1] mlm lm
trace(hatvalues)
hatvalues(Rohwer.mod, m=2)
trace: hatvalues(Rohwer.mod, m = 2)
Error in UseMethod(hatvalues) :
no applicable method for 'hatvalues' applied to an object of class
c('double', 'numeric')
hatvalues(Rohwer.mod)
trace: hatvalues(Rohwer.mod)
1 2 3 4 5 6
7 8
0.16700926 0.21845327 0.14173469 0.07314341 0.56821462 0.15432157
0.04530969 0.17661104
...
I'm still stumped on why with the extra argument m=2, R sees this
as an object of class c('double', 'numeric'). As well, I can't see
any way to debug this.
I'm not sure, but I think it is just the new class inflmlm applied
to inf in the formals of hatvalues.mlm confused the dispatch
mechanism. You would think the error message will call the offending
class not numeric double but that's above my pay grade...
You could probably put back the inflmlm class assignment with an
explicit call to UseMethod in hatvalues.mlm ?
Cheers
On Fri, Feb 10, 2012 at 2:35 PM, Michael Friendlyfrien...@yorku.ca wrote:
On 2/10/2012 4:09 PM, Henrik Bengtsson wrote:
So people may prefer to do the following:
hatvalues.mlm- function(model, m=1, infl, ...)
{
if (missing(infl)) {
infl- mlm.influence(model, m=m, do.coef=FALSE);
}
hat- infl$H
m- infl$m
names(hat)- if(m==1) infl$subsets else apply(infl$subsets,1,
paste, collapse=',')
hat
}
Thanks; I tried exactly that, but I still can't pass m=2 to the mlm method
through the generic
hatvalues(Rohwer.mod)
1 2 3 4 5 6 7
8
0.16700926 0.21845327 0.14173469 0.07314341 0.56821462 0.15432157 0.04530969
0.17661104
9 10 11 12 13 14 15
16
0.05131298 0.45161152 0.14542776 0.17050399 0.10374592 0.12649927 0.33246744
0.33183461
17 18 19 20 21 22 23
24
0.17320579 0.26353864 0.29835817 0.07880597 0.14023750 0.19380286 0.04455330
0.20641708
25 26 27 28 29 30 31
32
0.15712604 0.15333879 0.36726467 0.11189754 0.30426999 0.08655434 0.08921878
0.07320950
hatvalues(Rohwer.mod, m=2)
Error in UseMethod(hatvalues) :
no applicable method for 'hatvalues' applied to an object of class
c('double', 'numeric')
## This works:
hatvalues.mlm(Rohwer.mod, m=2)
... output snipped
hatvalues
function (model, ...)
UseMethod(hatvalues)
bytecode: 0x021339e4
environment: namespace:stats
-Michael
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele StreetWeb: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele StreetWeb: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
__
R-help@r-project.org 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] passing an extra argument to an S3 generic
Hi Michael,
Try the attached. The only change to your script is in the first line
where I explicitly tell hatvalues to use methods (the infmlm class
stays). I also commented out all your TESTME at the end.
source('mlminfl-testHELP.R')
Now this should have worked for you too. Let me know. Sorry about that
just remove the class. Had somewhat of a brain glitch when writing
the E-mail and wasn't clear.
Cheers
On Tue, Feb 14, 2012 at 8:05 AM, Michael Friendly frien...@yorku.ca wrote:
On 2/11/2012 12:00 PM, ilai wrote:
You are setting a new class (inflmlm) at the end of mlm.influence.
Remove that second to last line and enjoy your new S3 method.
Thanks for the suggestion, but it doesn't help -- I still get the same
behavior whether mlm.influence returns a classed object or not.
As well, I am defining print.inflmlm() and as.data.frame.inflmlm() methods
for these objects, so I do need mlm.influence to return a classed object.
My hatvalues.mlm is designed to be similar in structure to
stats::hatvalues.lm where the S3 generic is defined.
hatvalues.mlm - function(model, m=1, infl, ...)
{
if (missing(infl)) {
infl - mlm.influence(model, m=m, do.coef=FALSE);
}
hat - infl$H
m - infl$m
names(hat) - if(m==1) infl$subsets else apply(infl$subsets,1, paste,
collapse=',')
hat
}
hatvalues
function (model, ...)
UseMethod(hatvalues)
bytecode: 0x0326fd30
environment: namespace:stats
hatvalues.lm
function (model, infl = lm.influence(model, do.coef = FALSE),
...)
{
hat - infl$hat
names(hat) - names(infl$wt.res)
hat
}
bytecode: 0x0326de6c
environment: namespace:stats
The idea is that the infl= argument specifies a call to the computational
function, mlm.influence() in my case, just as lm.influence() does in the
stats package.
The logic of UseMethod is that it should dispatch on the class of the
*first* argument to the function, which in my test case is c(mlm, lm)
Rohwer.mod - lm(cbind(SAT, PPVT, Raven) ~ n+s+ns+na+ss, data=Rohwer2)
class(Rohwer.mod)
[1] mlm lm
trace(hatvalues)
hatvalues(Rohwer.mod, m=2)
trace: hatvalues(Rohwer.mod, m = 2)
Error in UseMethod(hatvalues) :
no applicable method for 'hatvalues' applied to an object of class
c('double', 'numeric')
hatvalues(Rohwer.mod)
trace: hatvalues(Rohwer.mod)
1 2 3 4 5 6 7
8
0.16700926 0.21845327 0.14173469 0.07314341 0.56821462 0.15432157 0.04530969
0.17661104
...
I'm still stumped on why with the extra argument m=2, R sees this
as an object of class c('double', 'numeric'). As well, I can't see
any way to debug this.
I'm not sure, but I think it is just the new class inflmlm applied
to inf in the formals of hatvalues.mlm confused the dispatch
mechanism. You would think the error message will call the offending
class not numeric double but that's above my pay grade...
You could probably put back the inflmlm class assignment with an
explicit call to UseMethod in hatvalues.mlm ?
Cheers
On Fri, Feb 10, 2012 at 2:35 PM, Michael Friendlyfrien...@yorku.ca
wrote:
On 2/10/2012 4:09 PM, Henrik Bengtsson wrote:
So people may prefer to do the following:
hatvalues.mlm- function(model, m=1, infl, ...)
{
if (missing(infl)) {
infl- mlm.influence(model, m=m, do.coef=FALSE);
}
hat- infl$H
m- infl$m
names(hat)- if(m==1) infl$subsets else apply(infl$subsets,1,
paste, collapse=',')
hat
}
Thanks; I tried exactly that, but I still can't pass m=2 to the mlm
method
through the generic
hatvalues(Rohwer.mod)
1 2 3 4 5 6
7
8
0.16700926 0.21845327 0.14173469 0.07314341 0.56821462 0.15432157
0.04530969
0.17661104
9 10 11 12 13 14
15
16
0.05131298 0.45161152 0.14542776 0.17050399 0.10374592 0.12649927
0.33246744
0.33183461
17 18 19 20 21 22
23
24
0.17320579 0.26353864 0.29835817 0.07880597 0.14023750 0.19380286
0.04455330
0.20641708
25 26 27 28 29 30
31
32
0.15712604 0.15333879 0.36726467 0.11189754 0.30426999 0.08655434
0.08921878
0.07320950
hatvalues(Rohwer.mod, m=2)
Error in UseMethod(hatvalues) :
no applicable method for 'hatvalues' applied to an object of class
c('double', 'numeric')
## This works:
hatvalues.mlm(Rohwer.mod, m=2)
... output snipped
hatvalues
function (model, ...)
UseMethod(hatvalues)
bytecode: 0x021339e4
environment: namespace:stats
-Michael
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York
Re: [R] passing an extra argument to an S3 generic
You are setting a new class (inflmlm) at the end of mlm.influence.
Remove that second to last line and enjoy your new S3 method.
I'm not sure, but I think it is just the new class inflmlm applied
to inf in the formals of hatvalues.mlm confused the dispatch
mechanism. You would think the error message will call the offending
class not numeric double but that's above my pay grade...
You could probably put back the inflmlm class assignment with an
explicit call to UseMethod in hatvalues.mlm ?
Cheers
On Fri, Feb 10, 2012 at 2:35 PM, Michael Friendly frien...@yorku.ca wrote:
On 2/10/2012 4:09 PM, Henrik Bengtsson wrote:
So people may prefer to do the following:
hatvalues.mlm- function(model, m=1, infl, ...)
{
if (missing(infl)) {
infl- mlm.influence(model, m=m, do.coef=FALSE);
}
hat- infl$H
m- infl$m
names(hat)- if(m==1) infl$subsets else apply(infl$subsets,1,
paste, collapse=',')
hat
}
Thanks; I tried exactly that, but I still can't pass m=2 to the mlm method
through the generic
hatvalues(Rohwer.mod)
1 2 3 4 5 6 7
8
0.16700926 0.21845327 0.14173469 0.07314341 0.56821462 0.15432157 0.04530969
0.17661104
9 10 11 12 13 14 15
16
0.05131298 0.45161152 0.14542776 0.17050399 0.10374592 0.12649927 0.33246744
0.33183461
17 18 19 20 21 22 23
24
0.17320579 0.26353864 0.29835817 0.07880597 0.14023750 0.19380286 0.04455330
0.20641708
25 26 27 28 29 30 31
32
0.15712604 0.15333879 0.36726467 0.11189754 0.30426999 0.08655434 0.08921878
0.07320950
hatvalues(Rohwer.mod, m=2)
Error in UseMethod(hatvalues) :
no applicable method for 'hatvalues' applied to an object of class
c('double', 'numeric')
## This works:
hatvalues.mlm(Rohwer.mod, m=2)
... output snipped
hatvalues
function (model, ...)
UseMethod(hatvalues)
bytecode: 0x021339e4
environment: namespace:stats
-Michael
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
__
R-help@r-project.org 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] passing an extra argument to an S3 generic
On 2/9/2012 6:24 PM, ilai wrote:
You do not provide mlm.influence() so your code can't be reproduced.
Or did you mean to put lm.influence() in the formals to your hatvalues.mlm ?
If yes, then 1) you have a typo 2) lm.influence doesn't allow you to
pass on arguments, maybe try influence.lm instead.
No, I've written an S3 method, influence.mlm and a computational method,
mlm.influence, both of which take an m= argument. I didn't post all the
code because I thought the question might have an easy answer based on
what I provided.
I include all the code and a test case in the attached .txt file that
can be sourced.
-Michael
Elai
On Thu, Feb 9, 2012 at 1:42 PM, Michael Friendlyfrien...@yorku.ca wrote:
I'm trying to write some functions extending influence measures to
multivariate linear models and also
allow subsets of size m=1 to be considered for deletion diagnostics. I'd
like these to work roughly parallel
to those functions for the univariate lm where only single case deletion
(m=1) diagnostics are considered.
Corresponding to stats::hatvalues.lm, the S3 method for class lm objects,
hatvalues-function (model, ...)
UseMethod(hatvalues)
hatvalues.lm-
function (model, infl = lm.influence(model, do.coef = FALSE),...)
{
hat- infl$hat
names(hat)- names(infl$wt.res)
hat
}
I have, for class mlm objects
hatvalues.mlm- function(model, m=1, infl=mlm.influence(model, m=m, do.coef
= FALSE), ...)
{
hat- infl$H
m- infl$m
names(hat)- if(m==1) infl$subsets else apply(infl$subsets,1, paste,
collapse=',')
hat
}
where mlm.influence() does the calculations, but also allows the m= argument
to specify subset size.
Yet when I test this I can't seem to pass the m= argument directly, so that
it gets stuffed in to the infl=
call to mlm.influence.
# fit an mlm
library(heplots)
Rohwer2- subset(Rohwer, subset=group==2)
rownames(Rohwer2)- 1:nrow(Rohwer2)
Rohwer.mod- lm(cbind(SAT, PPVT, Raven) ~ n+s+ns+na+ss, data=Rohwer2)
class(Rohwer.mod)
[1] mlm lm
## this doesn't work, as I would like it to, calling the hatvalues.mlm
method, but passing m=2:
hatvalues(Rohwer.mod, m=2)
Error in UseMethod(hatvalues) :
no applicable method for 'hatvalues' applied to an object of class
c('double', 'numeric')
I don't understand why this doesn't just call hatvalues.mlm, since
Rohwer.mod is of class mlm.
# These work -- calling hatvalues.mlm explicitly, or passing the infl=
argument with the call to
# mlm.influence
hatvalues.mlm(Rohwer.mod, m=2)
hatvalues(Rohwer.mod, infl=mlm.influence(Rohwer.mod,m=2))
Can someone help me understand what is wrong and how to make the .mlm method
allow m= to be passed
directly to the infl= computation?
thx,
-Michael
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele StreetWeb: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
__
R-help@r-project.org 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.
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele StreetWeb: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
# S3 method for class mlm
influence.mlm - function(model, m=1, do.coef=TRUE, ...)
mlm.influence(model, m=m, do.coef = do.coef, ...)
# main computation a la lm.influence
mlm.influence -
function (model, m=1, do.coef = TRUE, ...)
{
# helper functions
vec - function(M) {
R - matrix(M, ncol=1)
if (is.vector(M)) return(R)
nn-expand.grid(dimnames(M))[,2:1]
rownames(R) - apply(as.matrix(nn), 1, paste, collapse=:)
R
}
X - model.matrix(model)
data - model.frame(model)
Y - as.matrix(model.response(data))
r - ncol(Y)
n - nrow(X)
p - ncol(X)
labels - rownames(X)
call - model$call
B - coef(model)
E - residuals(model)
XPXI - solve(crossprod(X))
EPEI - solve(crossprod(E))
vB - vec(t(B))
S - crossprod(E)/(n-p);
V - solve(p*S) %x% crossprod(X)
subsets - t(combn(n, m))
nsub - nrow(subsets)
Beta - as.list(rep(0, nsub))
R - L - H - Q - as.list(rep(0, nsub))
CookD - as.vector(rep(0, nsub))
# FIXME: naive, direct computations can use qr() or update()
for (i in seq(nsub)) {
I - c(subsets[i,])
rows - which(!(1:n) %in% I)
XI - X[rows,]
YI - Y[rows,]
BI - solve(crossprod(XI)) %*% t(XI) %*% YI
EI - (Y - X %*% BI)[I, , drop=FALSE]
CookD[i] - t(vec(B - BI)) %*% V
Re: [R] passing an extra argument to an S3 generic
For these type of setups, I typically turn to default values, e.g.
hatvalues.mlm - function(model, m=1, infl=NULL, ...)
{
if (is.null(infl)) {
infl - mlm.influence(model, m=m, do.coef=FALSE);
}
hat - infl$H
m - infl$m
names(hat) - if(m==1) infl$subsets else apply(infl$subsets,1,
paste, collapse=',')
hat
}
So people may prefer to do the following:
hatvalues.mlm - function(model, m=1, infl, ...)
{
if (missing(infl)) {
infl - mlm.influence(model, m=m, do.coef=FALSE);
}
hat - infl$H
m - infl$m
names(hat) - if(m==1) infl$subsets else apply(infl$subsets,1,
paste, collapse=',')
hat
}
The downside with this approach is that args(fcn) doesn't reveal the
default behavior; instead you need to document it clearly in the
help(fcn).
My $.02
/H
On Fri, Feb 10, 2012 at 12:13 PM, Michael Friendly frien...@yorku.ca wrote:
On 2/9/2012 6:24 PM, ilai wrote:
You do not provide mlm.influence() so your code can't be reproduced.
Or did you mean to put lm.influence() in the formals to your hatvalues.mlm
?
If yes, then 1) you have a typo 2) lm.influence doesn't allow you to
pass on arguments, maybe try influence.lm instead.
No, I've written an S3 method, influence.mlm and a computational method,
mlm.influence, both of which take an m= argument. I didn't post all the
code because I thought the question might have an easy answer based on what
I provided.
I include all the code and a test case in the attached .txt file that
can be sourced.
-Michael
Elai
On Thu, Feb 9, 2012 at 1:42 PM, Michael Friendlyfrien...@yorku.ca
wrote:
I'm trying to write some functions extending influence measures to
multivariate linear models and also
allow subsets of size m=1 to be considered for deletion diagnostics.
I'd
like these to work roughly parallel
to those functions for the univariate lm where only single case deletion
(m=1) diagnostics are considered.
Corresponding to stats::hatvalues.lm, the S3 method for class lm
objects,
hatvalues-function (model, ...)
UseMethod(hatvalues)
hatvalues.lm-
function (model, infl = lm.influence(model, do.coef = FALSE), ...)
{
hat- infl$hat
names(hat)- names(infl$wt.res)
hat
}
I have, for class mlm objects
hatvalues.mlm- function(model, m=1, infl=mlm.influence(model, m=m,
do.coef
= FALSE), ...)
{
hat- infl$H
m- infl$m
names(hat)- if(m==1) infl$subsets else apply(infl$subsets,1, paste,
collapse=',')
hat
}
where mlm.influence() does the calculations, but also allows the m=
argument
to specify subset size.
Yet when I test this I can't seem to pass the m= argument directly, so
that
it gets stuffed in to the infl=
call to mlm.influence.
# fit an mlm
library(heplots)
Rohwer2- subset(Rohwer, subset=group==2)
rownames(Rohwer2)- 1:nrow(Rohwer2)
Rohwer.mod- lm(cbind(SAT, PPVT, Raven) ~ n+s+ns+na+ss, data=Rohwer2)
class(Rohwer.mod)
[1] mlm lm
## this doesn't work, as I would like it to, calling the hatvalues.mlm
method, but passing m=2:
hatvalues(Rohwer.mod, m=2)
Error in UseMethod(hatvalues) :
no applicable method for 'hatvalues' applied to an object of class
c('double', 'numeric')
I don't understand why this doesn't just call hatvalues.mlm, since
Rohwer.mod is of class mlm.
# These work -- calling hatvalues.mlm explicitly, or passing the infl=
argument with the call to
# mlm.influence
hatvalues.mlm(Rohwer.mod, m=2)
hatvalues(Rohwer.mod, infl=mlm.influence(Rohwer.mod,m=2))
Can someone help me understand what is wrong and how to make the .mlm
method
allow m= to be passed
directly to the infl= computation?
thx,
-Michael
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
__
R-help@r-project.org 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.
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
__
R-help@r-project.org 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.
__
R-help@r-project.org 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] passing an extra argument to an S3 generic
On 2/10/2012 4:09 PM, Henrik Bengtsson wrote:
So people may prefer to do the following:
hatvalues.mlm- function(model, m=1, infl, ...)
{
if (missing(infl)) {
infl- mlm.influence(model, m=m, do.coef=FALSE);
}
hat- infl$H
m- infl$m
names(hat)- if(m==1) infl$subsets else apply(infl$subsets,1,
paste, collapse=',')
hat
}
Thanks; I tried exactly that, but I still can't pass m=2 to the mlm
method through the generic
hatvalues(Rohwer.mod)
1 2 3 4 5
6 7 8
0.16700926 0.21845327 0.14173469 0.07314341 0.56821462 0.15432157
0.04530969 0.17661104
9 10 11 12 13
14 15 16
0.05131298 0.45161152 0.14542776 0.17050399 0.10374592 0.12649927
0.33246744 0.33183461
17 18 19 20 21
22 23 24
0.17320579 0.26353864 0.29835817 0.07880597 0.14023750 0.19380286
0.04455330 0.20641708
25 26 27 28 29
30 31 32
0.15712604 0.15333879 0.36726467 0.11189754 0.30426999 0.08655434
0.08921878 0.07320950
hatvalues(Rohwer.mod, m=2)
Error in UseMethod(hatvalues) :
no applicable method for 'hatvalues' applied to an object of class
c('double', 'numeric')
## This works:
hatvalues.mlm(Rohwer.mod, m=2)
... output snipped
hatvalues
function (model, ...)
UseMethod(hatvalues)
bytecode: 0x021339e4
environment: namespace:stats
-Michael
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele StreetWeb: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
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Re: [R] passing an extra argument to an S3 generic
You do not provide mlm.influence() so your code can't be reproduced.
Or did you mean to put lm.influence() in the formals to your hatvalues.mlm ?
If yes, then 1) you have a typo 2) lm.influence doesn't allow you to
pass on arguments, maybe try influence.lm instead.
Elai
On Thu, Feb 9, 2012 at 1:42 PM, Michael Friendly frien...@yorku.ca wrote:
I'm trying to write some functions extending influence measures to
multivariate linear models and also
allow subsets of size m=1 to be considered for deletion diagnostics. I'd
like these to work roughly parallel
to those functions for the univariate lm where only single case deletion
(m=1) diagnostics are considered.
Corresponding to stats::hatvalues.lm, the S3 method for class lm objects,
hatvalues -function (model, ...)
UseMethod(hatvalues)
hatvalues.lm -
function (model, infl = lm.influence(model, do.coef = FALSE), ...)
{
hat - infl$hat
names(hat) - names(infl$wt.res)
hat
}
I have, for class mlm objects
hatvalues.mlm - function(model, m=1, infl=mlm.influence(model, m=m, do.coef
= FALSE), ...)
{
hat - infl$H
m - infl$m
names(hat) - if(m==1) infl$subsets else apply(infl$subsets,1, paste,
collapse=',')
hat
}
where mlm.influence() does the calculations, but also allows the m= argument
to specify subset size.
Yet when I test this I can't seem to pass the m= argument directly, so that
it gets stuffed in to the infl=
call to mlm.influence.
# fit an mlm
library(heplots)
Rohwer2 - subset(Rohwer, subset=group==2)
rownames(Rohwer2)- 1:nrow(Rohwer2)
Rohwer.mod - lm(cbind(SAT, PPVT, Raven) ~ n+s+ns+na+ss, data=Rohwer2)
class(Rohwer.mod)
[1] mlm lm
## this doesn't work, as I would like it to, calling the hatvalues.mlm
method, but passing m=2:
hatvalues(Rohwer.mod, m=2)
Error in UseMethod(hatvalues) :
no applicable method for 'hatvalues' applied to an object of class
c('double', 'numeric')
I don't understand why this doesn't just call hatvalues.mlm, since
Rohwer.mod is of class mlm.
# These work -- calling hatvalues.mlm explicitly, or passing the infl=
argument with the call to
# mlm.influence
hatvalues.mlm(Rohwer.mod, m=2)
hatvalues(Rohwer.mod, infl=mlm.influence(Rohwer.mod,m=2))
Can someone help me understand what is wrong and how to make the .mlm method
allow m= to be passed
directly to the infl= computation?
thx,
-Michael
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
__
R-help@r-project.org 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.
__
R-help@r-project.org mailing list
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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.
