Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix doc/help references to bit-rotted variables x and v #28855

Merged
merged 1 commit into from
Aug 23, 2018
Merged

Fix doc/help references to bit-rotted variables x and v #28855

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 5 additions & 5 deletions stdlib/Statistics/src/Statistics.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -248,7 +248,7 @@ end
Compute the sample variance of a collection `v` with known mean(s) `m`,
optionally over the given dimensions. `m` may contain means for each dimension of
`v`. If `corrected` is `true`, then the sum is scaled with `n-1`,
whereas the sum is scaled with `n` if `corrected` is `false` where `n = length(x)`.
whereas the sum is scaled with `n` if `corrected` is `false` where `n = length(v)`.

!!! note
If array contains `NaN` or [`missing`](@ref) values, the result is also
Expand Down Expand Up @@ -278,7 +278,7 @@ The algorithm will return an estimator of the generative distribution's variance
under the assumption that each entry of `v` is an IID drawn from that generative
distribution. This computation is equivalent to calculating `sum(abs2, v - mean(v)) /
(length(v) - 1)`. If `corrected` is `true`, then the sum is scaled with `n-1`,
whereas the sum is scaled with `n` if `corrected` is `false` where `n = length(x)`.
whereas the sum is scaled with `n` if `corrected` is `false` where `n = length(v)`.
The mean `mean` over the region may be provided.

!!! note
Expand Down Expand Up @@ -345,7 +345,7 @@ deviation under the assumption that each entry of `v` is an IID drawn from that
distribution. This computation is equivalent to calculating `sqrt(sum((v - mean(v)).^2) /
(length(v) - 1))`. A pre-computed `mean` may be provided. If `corrected` is `true`,
then the sum is scaled with `n-1`, whereas the sum is scaled with `n` if `corrected` is
`false` where `n = length(x)`.
`false` where `n = length(v)`.

!!! note
If array contains `NaN` or [`missing`](@ref) values, the result is also
Expand Down Expand Up @@ -376,7 +376,7 @@ std(iterable; corrected::Bool=true, mean=nothing) =
Compute the sample standard deviation of a vector `v`
with known mean `m`. If `corrected` is `true`,
then the sum is scaled with `n-1`, whereas the sum is
scaled with `n` if `corrected` is `false` where `n = length(x)`.
scaled with `n` if `corrected` is `false` where `n = length(v)`.

!!! note
If array contains `NaN` or [`missing`](@ref) values, the result is also
Expand Down Expand Up @@ -882,7 +882,7 @@ probabilities `p` on the interval [0,1]. The keyword argument `sorted` indicates
`itr` can be assumed to be sorted.

Quantiles are computed via linear interpolation between the points `((k-1)/(n-1), v[k])`,
for `k = 1:n` where `n = length(v)`. This corresponds to Definition 7 of Hyndman and Fan
for `k = 1:n` where `n = length(itr)`. This corresponds to Definition 7 of Hyndman and Fan
(1996), and is the same as the R default.

!!! note
Expand Down