weights= argument for froll{mean,sum,...}

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Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
35/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
r
Domain
data

Research direction

Start with the froll{mean,sum,...} entry points and compare them with the frollapply workaround using stats::weighted.mean shown in the issue. Check the x and w example first, then establish expected weighted results for the rolling functions; done means a weights= argument supports the requested froll operations.

Written by the indexing model from the issue text.

Description

feature request froll

Weighted means are pretty common in my experience.

The current workaround is pretty awkward (I might be using a weird approach, CMIIW):

x = 1:10
w = 10:1
frollapply(seq_along(x), n = 3, function(i) stats::weighted.mean(x[i], w[i]))
#  [1]       NA       NA 1.925926 2.916667 3.904762 4.888889 5.866667 6.833333 7.777778 8.666667
Dominant language
R
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Avg merge
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Merged PRs (30d)
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