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Murray Jorgensen

2006-Aug-01 04:08 UTC

[R] Fitting models in a loop

If I want to display a few polynomial regression fits I can do something 
like

for (i in 1:6) {
	mod <- lm(y ~ poly(x,i))
	print(summary(mod))
	}

Suppose that I don't want to over-write the fitted model objects, 
though. How do I create a list of blank fitted model objects for later 
use in a loop?

Murray Jorgensen
-- 
Dr Murray Jorgensen      http://www.stats.waikato.ac.nz/Staff/maj.html
Department of Statistics, University of Waikato, Hamilton, New Zealand
Email: maj at waikato.ac.nz                                Fax 7 838 4155
Phone  +64 7 838 4773 wk    Home +64 7 825 0441    Mobile 021 1395 862

Bill.Venables at csiro.au

2006-Aug-01 05:16 UTC

head link

[R] Fitting models in a loop

Murray,

Here is a general paradigm I tend to use for such problems.  It extends
to fairly general model sequences, including different responses, &c

First a couple of tiny, tricky but useful functions:

subst <- function(Command, ...) do.call("substitute", list(Command,
list(...)))

abut <- function(...)  ## jam things tightly together
  do.call("paste", c(lapply(list(...), as.character), sep =
""))

Name <- function(...) as.name(do.call("abut", list(...)))

Now the gist.

fitCommand <- quote({
	MODELi <- lm(y ~ poly(x, degree = i), theData)
	print(summary(MODELi))
})
for(i in 1:6) {
	thisCommand <- subst(fitCommand, MODELi = Name("model_", i), i i)
	print(thisCommand)  ## only as a check
	eval(thisCommand)
}

At this point you should have the results and

objects(pat = "^model_")

should list the fitted model objects, all of which can be updated,
summarised, plotted, &c, because the information on their construction
is all embedded in the call.

Bill.

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Murray Jorgensen
Sent: Tuesday, 1 August 2006 2:09 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Fitting models in a loop

If I want to display a few polynomial regression fits I can do something

like

for (i in 1:6) {
	mod <- lm(y ~ poly(x,i))
	print(summary(mod))
	}

Suppose that I don't want to over-write the fitted model objects, 
though. How do I create a list of blank fitted model objects for later 
use in a loop?

Murray Jorgensen
-- 
Dr Murray Jorgensen      http://www.stats.waikato.ac.nz/Staff/maj.html
Department of Statistics, University of Waikato, Hamilton, New Zealand
Email: maj at waikato.ac.nz                                Fax 7 838 4155
Phone  +64 7 838 4773 wk    Home +64 7 825 0441    Mobile 021 1395 862

______________________________________________
R-help at 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.

Gesmann, Markus

2006-Aug-01 09:58 UTC

head link

[R] Fitting models in a loop

Murray,

How about creating an empty list and filling it during your loop:

 mod <- list()
 for (i in 1:6) {
	mod[[i]] <- lm(y ~ poly(x,i))
	print(summary(mod[[i]]))
	}

All your models are than stored in one object and you can use lapply to
do something on them, like:
 lapply(mod, summary) or lapply(mod, coef)


Kind Regards

Markus Gesmann
FPMA
Lloyd's Market Analysis
Lloyd's * One Lime Street * London * EC3M 7HA
Telephone +44 (0)20 7327 6472
Facsimile +44 (0)20 7327 5718
http://www.lloyds.com


-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of
Bill.Venables at csiro.au
Sent: 01 August 2006 06:16
To: maj at waikato.ac.nz; r-help at stat.math.ethz.ch
Subject: Re: [R] Fitting models in a loop


Murray,

Here is a general paradigm I tend to use for such problems.  It extends
to fairly general model sequences, including different responses, &c

First a couple of tiny, tricky but useful functions:

subst <- function(Command, ...) do.call("substitute", list(Command,
list(...)))

abut <- function(...)  ## jam things tightly together
  do.call("paste", c(lapply(list(...), as.character), sep =
""))

Name <- function(...) as.name(do.call("abut", list(...)))

Now the gist.

fitCommand <- quote({
	MODELi <- lm(y ~ poly(x, degree = i), theData)
	print(summary(MODELi))
})
for(i in 1:6) {
	thisCommand <- subst(fitCommand, MODELi = Name("model_", i), i i)
	print(thisCommand)  ## only as a check
	eval(thisCommand)
}

At this point you should have the results and

objects(pat = "^model_")

should list the fitted model objects, all of which can be updated,
summarised, plotted, &c, because the information on their construction
is all embedded in the call.

Bill.

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Murray Jorgensen
Sent: Tuesday, 1 August 2006 2:09 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Fitting models in a loop

If I want to display a few polynomial regression fits I can do something

like

for (i in 1:6) {
	mod <- lm(y ~ poly(x,i))
	print(summary(mod))
	}

Suppose that I don't want to over-write the fitted model objects, 
though. How do I create a list of blank fitted model objects for later 
use in a loop?

Murray Jorgensen
-- 
Dr Murray Jorgensen      http://www.stats.waikato.ac.nz/Staff/maj.html
Department of Statistics, University of Waikato, Hamilton, New Zealand
Email: maj at waikato.ac.nz                                Fax 7 838 4155
Phone  +64 7 838 4773 wk    Home +64 7 825 0441    Mobile 021 1395 862

______________________________________________
R-help at 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.

______________________________________________
R-help at 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.
**********************************************************************
The information in this E-Mail and in any attachments is CON...{{dropped}}

Bill.Venables at csiro.au

2006-Aug-01 23:28 UTC

head link

[R] Fitting models in a loop

Markus Gesmann writes:
> Murray,
> 
> How about creating an empty list and filling it during your loop:
> 
>  mod <- list()
>  for (i in 1:6) {
> 	  mod[[i]] <- lm(y ~ poly(x,i))
> 	  print(summary(mod[[i]]))
> 	  }
> 
> All your models are than stored in one object and you can use lapply
to> do something on them, like:
>  lapply(mod, summary) or lapply(mod, coef)
I think it is important to see why this deceptively simple 
solution does not achieve the result that Murray wanted.

Take any fitted model object, say mod[[4]].  For this object the 
formula component of the call will be, literally,  y ~ poly(x, i), 
and not y ~ poly(x, 4), as would be required to use the object,
e.g. for prediction.  In fact all objects have the same formula.

You could, of course, re-create i and some things would be OK, 
but getting pretty messy.

You would still have a problem if you wanted to plot the fit with 
termplot(), for example, as it would try to do a two-dimensional 
plot of the component if both arguments to poly were variables.
> 
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of
> Bill.Venables at csiro.au
> Sent: 01 August 2006 06:16
> To: maj at waikato.ac.nz; r-help at stat.math.ethz.ch
> Subject: Re: [R] Fitting models in a loop
> 
> 
> Murray,
> 
> Here is a general paradigm I tend to use for such problems.  It
extends> to fairly general model sequences, including different responses, &c
> 
> First a couple of tiny, tricky but useful functions:
> 
> subst <- function(Command, ...) do.call("substitute",
list(Command,
> list(...)))
> 
> abut <- function(...)  ## jam things tightly together
>   do.call("paste", c(lapply(list(...), as.character), sep =
""))
> 
> Name <- function(...) as.name(do.call("abut", list(...)))
> 
> Now the gist.
> 
> fitCommand <- quote({
> 	  MODELi <- lm(y ~ poly(x, degree = i), theData)
> 	  print(summary(MODELi))
> })
> for(i in 1:6) {
> 	  thisCommand <- subst(fitCommand, MODELi = Name("model_",
i), i
> i)
> 	  print(thisCommand)  ## only as a check
> 	  eval(thisCommand)
> }
> 
> At this point you should have the results and
> 
> objects(pat = "^model_")
> 
> should list the fitted model objects, all of which can be updated,
> summarised, plotted, &c, because the information on their construction
> is all embedded in the call.
> 
> Bill.
> 
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Murray
Jorgensen> Sent: Tuesday, 1 August 2006 2:09 PM
> To: r-help at stat.math.ethz.ch
> Subject: [R] Fitting models in a loop
> 
> If I want to display a few polynomial regression fits I can do
something> 
> like
> 
> for (i in 1:6) {
> 	  mod <- lm(y ~ poly(x,i))
> 	  print(summary(mod))
> 	  }
> 
> Suppose that I don't want to over-write the fitted model objects, 
> though. How do I create a list of blank fitted model objects for later
> use in a loop?
> 
> Murray Jorgensen
> --

Bill.Venables at csiro.au

2006-Aug-02 03:21 UTC

head link

[R] Fitting models in a loop

This (below) also runs into trouble if you try to predict with new data
since you have no rule for re-constructing the formula.  Also, you can't
plot the term as a single contributor to the linear predictor with
termplot().

I'm sure given enough ingenuity you can get round these two, but why
avoid the language manipulation solution, when it does the lot?

Bill.


-----Original Message-----
From: Gabor Grothendieck [mailto:ggrothendieck at gmail.com] 
Sent: Wednesday, 2 August 2006 12:01 PM
To: Venables, Bill (CMIS, Cleveland)
Cc: Markus.Gesmann at lloyds.com; maj at waikato.ac.nz;
r-help at stat.math.ethz.ch
Subject: Re: [R] Fitting models in a loop

A simple way around this is to pass it as a data frame.
In the code below the only change we made was to change
the formula from y ~ poly(x, i) to y ~ . and pass poly(x,i)
in a data frame as argument 2 of lm:

# test data
set.seed(1)
x <- 1:10
y <- x^3 + rnorm(10)

# run same code except change the lm call
mod <- list()
for (i in 1:3) {
        mod[[i]] <- lm(y ~., data.frame(poly(x, i)))
        print(summary(mod[[i]]))
}

After running the above we can test that it works:
> for(i in 1:3) print(formula(mod[[i]]))y ~ X1
y ~ X1 + X2
y ~ X1 + X2 + X3

On 8/1/06, Bill.Venables at csiro.au <Bill.Venables at csiro.au>
wrote:>
> Markus Gesmann writes:
>
> > Murray,
> >
> > How about creating an empty list and filling it during your loop:
> >
> >  mod <- list()
> >  for (i in 1:6) {
> >         mod[[i]] <- lm(y ~ poly(x,i))
> >         print(summary(mod[[i]]))
> >         }
> >
> > All your models are than stored in one object and you can use lapply
> to
> > do something on them, like:
> >  lapply(mod, summary) or lapply(mod, coef)
>
> I think it is important to see why this deceptively simple
> solution does not achieve the result that Murray wanted.
>
> Take any fitted model object, say mod[[4]].  For this object the
> formula component of the call will be, literally,  y ~ poly(x, i),
> and not y ~ poly(x, 4), as would be required to use the object,
> e.g. for prediction.  In fact all objects have the same formula.
>
> You could, of course, re-create i and some things would be OK,
> but getting pretty messy.
>
> You would still have a problem if you wanted to plot the fit with
> termplot(), for example, as it would try to do a two-dimensional
> plot of the component if both arguments to poly were variables.
>
> >
> > -----Original Message-----
> > From: r-help-bounces at stat.math.ethz.ch
> > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of
> > Bill.Venables at csiro.au
> > Sent: 01 August 2006 06:16
> > To: maj at waikato.ac.nz; r-help at stat.math.ethz.ch
> > Subject: Re: [R] Fitting models in a loop
> >
> >
> > Murray,
> >
> > Here is a general paradigm I tend to use for such problems.  It
> extends
> > to fairly general model sequences, including different responses,
&c
> >
> > First a couple of tiny, tricky but useful functions:
> >
> > subst <- function(Command, ...) do.call("substitute",
list(Command,
> > list(...)))
> >
> > abut <- function(...)  ## jam things tightly together
> >   do.call("paste", c(lapply(list(...), as.character), sep =
""))
> >
> > Name <- function(...) as.name(do.call("abut", list(...)))
> >
> > Now the gist.
> >
> > fitCommand <- quote({
> >         MODELi <- lm(y ~ poly(x, degree = i), theData)
> >         print(summary(MODELi))
> > })
> > for(i in 1:6) {
> >         thisCommand <- subst(fitCommand, MODELi =
Name("model_", i),
i> > > i)
> >         print(thisCommand)  ## only as a check
> >         eval(thisCommand)
> > }
> >
> > At this point you should have the results and
> >
> > objects(pat = "^model_")
> >
> > should list the fitted model objects, all of which can be updated,
> > summarised, plotted, &c, because the information on their
construction> > is all embedded in the call.
> >
> > Bill.
> >
> > -----Original Message-----
> > From: r-help-bounces at stat.math.ethz.ch
> > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Murray
> Jorgensen
> > Sent: Tuesday, 1 August 2006 2:09 PM
> > To: r-help at stat.math.ethz.ch
> > Subject: [R] Fitting models in a loop
> >
> > If I want to display a few polynomial regression fits I can do
> something
> >
> > like
> >
> > for (i in 1:6) {
> >         mod <- lm(y ~ poly(x,i))
> >         print(summary(mod))
> >         }
> >
> > Suppose that I don't want to over-write the fitted model objects,
> > though. How do I create a list of blank fitted model objects for
later>
> > use in a loop?
> >
> > Murray Jorgensen
> > --
>
> ______________________________________________
> R-help at 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.
>

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