[R] zero weights in weighted.mean

Sorkin, John
Wed, 14 Jul 2021 17:43:11 -0000

Gentlemen,

At the risk of beating a dead horse, but in he spirit of learning more about R,
aren't the two expressions functionally the same? One drops values where
weight is zero. The other (in the case where we and infinity * 0, something one
would not expect to see in data) also drops data as in R infinity * 0 = Nan. In
either case the observation would be dropped. I am certain I am missing
something, but I don't know what I am missing.

John

John David Sorkin M.D., Ph.D.
Professor of Medicine
University of Maryland School of Medicine
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University of Maryland School of Medicine Division of Gerontology, Geriatrics
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________________________________________
From: R-help <r-help-bounces at r-project.org> on behalf of G?ran Brostr?m
<goran.brostrom at umu.se>
Sent: Wednesday, July 14, 2021 10:46 AM
To: Duncan Murdoch; r-help at r-project.org
Subject: Re: [R] zero weights in weighted.mean



Den 2021-07-14 kl. 13:16, skrev Duncan Murdoch:
> On 14/07/2021 6:00 a.m., G?ran Brostr?m wrote:
>> I wonder about the last sentence in the Details section of the
>> documentation of 'weighted.mean':
>>
>> "However, zero weights _are_ handled specially and the
corresponding ?x?
>> values are omitted from the sum."
>>
>> The return value of weighted.mean.default is
>>
>> sum((x * w)[w != 0])/sum(w)
>>
>> and indeed, it looks as if zero weights are getting special treatment,
>> but what is wrong with the alternative (equivalent?) expression
>>
>> sum(x * w) / sum(w)?
>>
>> Is it a good idea to remove zeros from a vector before applying
'sum' to
>> it? I don't think so. Anyway, the sentence in the documentation
seems to
>> be uncalled for.
>
> Inf*0 is not zero.  Setting weights to zero on infinite observations (or
> NA, or NaN) will give different results in your two expressions.

Thanks, agreed.

G,

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