>>>>> Martin Maechler <maech...@lynne.stat.math.ethz.ch>
>>>>> on Fri, 10 Apr 2015 16:28:06 +0200 writes:
> I'm proposing to add something like this to the stats
> package :
> ----------------------------------------------------------
> ### "The" sigma in lm/nls - "like" models:
> sigma <- function(object, ...) UseMethod("sigma")
> ## works whenever deviance(), nobs() and coef() do fine:
> sigma.default <- function (object, use.fallback=TRUE, ...)
> sqrt(deviance(object, ...) /
> (nobs(object, use.fallback=use.fallback) -
length(coef(object))))
> ----------------------------------------------------------
> [Yes, even though I am known to love S4 classes, and also
> methods, I propose an S3 generic here because it should go
> along with other typical S3 generics and methods, such as
> coef(), vcov(), ... ]
> The main reason/motivation for (something like) this is to
> provide encapsulation / abstraction for the following :
> Different (S3 and S4) fitted model objects use different
> ways to store the \hat\sigma (or \sqrt{\hat{\sigma^2}} -
> formally not quite the same !) as part of their object,
> and if I use methods which compare models, putting these
> into tables, etc, it is much nicer to use sigma(.) instead
> of having to use model-specific extractors.
No reaction at all.... which also means no opposition...
so I'll commit this to R-devel (--> R 3.3.0 in about one year),
and probably will live with the consequences :-)
Martin
> If I'm searching in our large collection of installed
> packages, I'm seeing
>> help.search("^sigma$")
> Help files with alias or concept or title matching ‘^sigma$’ using regular
> expression matching:
> AdaptFitOS::sigma Extract estimated varying residual variance
> Aliases: sigma
> distrEllipse::MVNormParameter-class
> Paramter of a multivariate normal distribution
> Aliases: sigma
> dlmodeler::dlmodeler.fit Fitting function for a model (MLE, MSE, MAD,
sigma)
> Concepts: sigma
> elliptic::WeierstrassP Weierstrass P and related functions
> Aliases: sigma
> gcExplorer::sigma E. coli Sigma Factors and Global Regulators
> Aliases: sigma
> investr::Sigma Extract residual standard error
> Aliases: Sigma
> lme4::sigma Extract residual standard error
> Aliases: sigma
> mbest::predict.mhglm Prediction
> Aliases: sigma
> nlmeU::sigma Extract scale parameter sigma from a model fit
> Aliases: sigma
> numbers::sigma Divisor Functions
> Aliases: sigma
> pmclust::PARAM A Set of Parameters in Model-Based Clustering.
> Aliases: SIGMA
> qualityTools::sigma Get and set methods
> Aliases: sigma
> robustbase::sigma Extract Residual Standard Error 'Sigma'
> Aliases: sigma
> rugarch::uGARCHfit-class class: Univariate GARCH Fit Class
> Aliases: sigma
> shapes::distCholesky Internal function(s)
> Aliases: sigma
> which also shows to the curious why I am making this
> proposition: I'm co-author of both the 'lme4' and 'robustbase' packages
> which already make use of this.
> Note that the default method would already work for
> lm(), nls(), and (some) glm() model fits.
> It may still make sense to use a slightly faster more explicit
> sigma.ls() method, but that's not the topic of this
> conversation, I think.
> Martin Maechler,
> ETH Zurich and R Core
> ______________________________________________
> R-devel@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
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