Also at the Julia REPL:
julia> apropos("standard deviation")
randn!
stdm
std
randn
help?> std
search: std stdm STDIN STDOUT STDERR setdiff setdiff! hist2d hist2d! stride
strides StridedArray StridedVector StridedMatrix StridedVecOrMat redirect_stdin
std(v[, region])
Compute the sample standard deviation of a vector or array v, optionally
along dimensions in region. The algorithm returns an estimator of the generative
distribution's standard deviation under the assumption that each entry of
v is an IID drawn from that generative distribution. This computation is
equivalent to
calculating sqrt(sum((v - mean(v)).^2) / (length(v) - 1)). Note: Julia
does not ignore NaN values in the computation. For applications requiring the
handling of
missing data, the DataArray package is recommended.
Having said this, documentation always needs improvements and is
certainly not on Matlab's level of completeness. Please contribute
where you find it lacking. See
https://github.com/JuliaLang/julia/blob/master/CONTRIBUTING.md#improving-documentation
On Fri, 2016-02-12 at 09:18, NotSoRecentConvert <[email protected]> wrote:
> You can even download the entire thing as a PDF, HTML, or EPUB if you want
> to highlight, annotate, or bookmark your most searched functions. Look in
> the lower right of the page for "v: latest" and click it for more options.
>
> On Friday, February 12, 2016 at 8:03:27 AM UTC+1, Lutfullah Tomak wrote:
>>
>> There is this one
>>
>> http://docs.julialang.org/en/release-0.4/stdlib/math/#Base.std
>>
>> Instead of google, I use this manual for search.
>>
>>
