[R] Forcing coefficents in lm(), recursive residuals, etc.

[Spencer Graves]

	  I know nothing about recresid, but does the following help:

 > x <- 1:4
 > set.seed(1)
 > DF <- data.frame(x=x, y=x+rnorm(4))
 > fit <- lm(y~offset(x), DF)
 > recresid(fit)
[1] 1.2799320 0.7232336 3.4826581
 >
	  spencer graves

Rick Ram wrote:

> Hi all,
> Just to clarify, I know that the predict() function would the normal
> avenue for applying a model but the problem is that I need to
> calculate recursive residuals, and the recresid() function needs an
> object with class "lm".
> Best,
> R.
> 
> On 28/07/05, Rick Ram <r.ramyar at gmail.com> wrote:
> 
>>Sorry guys, resending this - none of my posts have gone through
>>because HTML emails where not being delivered... sending this
>>plaintext now!
>>
>>On 28/07/05, Rick Ram <r.ramyar at gmail.com> wrote:
>>
>>>Resending cos I think this didn't get through for some reason... apologies
>>>if it arrives twice!
>>>
>>>
>>>---------- Forwarded message ----------
>>>From: Rick Ram < r.ramyar at gmail.com>
>>>Date: 28-Jul-2005 18:03
>>>Subject: Forcing coefficents in lm(), recursive residuals, etc.
>>>To: R-help <r-help at stat.math.ethz.ch >
>>>
>>>Hello all,
>>>
>>>Does anyone know how to constrain/force specific coefficients when running
>>>lm()?
>>>
>>>I need to run recresid() {strucchange package} on the residuals of
>>>forecast.lm, but forecast.lm's coefficients must be determined by
>>>parameter.estimation.lm
>>>
>>>I could estimate forecast.lm without lm() and use some other kind of
>>>optimisation, but recresid() requires an object with class lm.  recresid()
>>>allows you to specify a formula, rather than an lm object, but it looks like
>>>coefficients are estimated this way too and can't be forced.
>>>
>>>Here is a bit of code to compensate for my poor explanation:.
>>>
>>># Estimate the coefficients of model
>>>parameter.estimation.lm = lm(formula = y ~ x1 + x2, data =
>>>estimation.dataset)
>>># How do I force the coefficients in forecast.lm to the coeff estimation
>>>from parameter.estimation.lm??
>>>
>>>forecast.lm = lm(formula = y ~ x1 + x2, data = forecast.dataset)
>>># Because I need recursive residuals from the application of the
>>>coefficients from parameter.estimation.lm to a different dataset
>>>recresid(forecast.lm)
>>>
>>>Thanks in advance guys,
>>>
>>>R.
>>
> 
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