From @nnoporc| @end|ng |rom gm@||@com  Wed Feb 20 18:49:38 2019
From: @nnoporc| @end|ng |rom gm@||@com (PatrickT)
Date: Thu, 21 Feb 2019 01:49:38 +0800
Subject: [Rd] Documentation for sd (stats) + suggestion
In-Reply-To: <SYBPR01MB393143B27389E5C23E28F729CD7C0@SYBPR01MB3931.ausprd01.prod.outlook.com>
References: <CAJOE-h3w1Qei99Czqcn=0MB=GiMFUvX3Fdtq-E3yJnGmBNyJNg@mail.gmail.com>
 <9ea52c6ff077403dae73c4b155fbc793@GBDCVPEXC08.corp.lgc-group.com>
 <SYBPR01MB393143B27389E5C23E28F729CD7C0@SYBPR01MB3931.ausprd01.prod.outlook.com>
Message-ID: <CAJOE-h3T98PoJ+53iNEBAttN5N2TV1Sh1cxQW_srQpqPJ8Kdrw@mail.gmail.com>

Indeed. Thanks for your suggestions.

To elaborate briefly. The ``quantile`` function offers 9 types of methods.
The ``sd`` function only one. The ``mad`` function offers ways to tweak the
bias correction. The ``sd`` function doesn't.

Are there good reasons against adding features to ``sd``? after all it must
be one of the most popular stats out there.

Moreover the default ``sd`` function, which divides by n-1, is not well
founded like the variance is. It's still biased for repeated small
samples...

While it's easy to roll your own function, I don't think we can expect
beginners to write something like:

sdp = function(x) sqrt(sum((x-mean(x))^2)/length(x))


On Wed, Feb 20, 2019 at 9:00 AM Dario Strbenac <dstr7320 at uni.sydney.edu.au>
wrote:

> Good day,
>
> It is implemented by the CRAN package multicon. The function is named
> popsd. But it does seem like something R should provide without creating a
> package dependency.
>
> --------------------------------------
> Dario Strbenac
> University of Sydney
> Camperdown NSW 2050
> Australia
> ______________________________________________
> R-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>

	[[alternative HTML version deleted]]



[Rd] Documentation for sd (stats) + suggestion
PatrickT