7: alpha=1, beta=1 (Julia, R and NumPy default, Excel PERCENTILE and PERCENTILE.INC, Python 'inclusive') 6: alpha=0, beta=0 (Excel PERCENTILE.EXC, Python default, Stata altdef) The keyword arguments alpha and beta correspond to the same parameters in Hyndman and Fan, setting them to different values allows to calculate quantiles with any of the methods 4-9 defined in this paper: This corresponds to Definition 7 of Hyndman and Fan (1996), and is the same as the R and NumPy default. (If not provided, a new output array is created.) The keyword argument sorted indicates whether v can be assumed to be sorted if false (the default), then the elements of v will be partially sorted in-place.īy default ( alpha = beta = 1), quantiles are computed via linear interpolation between the points ((k-1)/(n-1), v), for k = 1:n where n = length(v). If p is a vector, an optional output array q may also be specified. Quantile!( v::AbstractVector, p sorted=false, alpha::Real=1.0, beta::Real=alpha)Ĭompute the quantile(s) of a vector v at a specified probability or vector or tuple of probabilities p on the interval. Reporting and analyzing crashes (segfaults).
printf() and stdio in the Julia runtime.
Noteworthy Differences from other Languages.Multi-processing and Distributed Computing.Mathematical Operations and Elementary Functions.