Robust Statistics

Robust Statistics

StatsBase.trimFunction.
trim(x; prop=0.0, count=0)

Return a copy of x with either count or proportion prop of the highest and lowest elements removed. To compute the trimmed mean of x use mean(trim(x)); to compute the variance use trimvar(x) (see trimvar).

Example

julia> trim([1,2,3,4,5], prop=0.2)
3-element Array{Int64,1}:
 2
 3
 4
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StatsBase.winsorFunction.
winsor(x; prop=0.0, count=0)

Return a copy of x with either count or proportion prop of the lowest elements of x replaced with the next-lowest, and an equal number of the highest elements replaced with the previous-highest. To compute the Winsorized mean of x use mean(winsor(x)).

Example

julia> winsor([1,2,3,4,5], prop=0.2)
5-element Array{Int64,1}:
 2
 2
 3
 4
 4
source
StatsBase.trimvarFunction.
trimvar(x; prop=0.0, count=0)

Compute the variance of the trimmed mean of x. This function uses the Winsorized variance, as described in Wilcox (2010).

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