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spat.med

Spatial median for Euclidean data


Description

Spatial median for Euclidean data.

Usage

spat.med(x, tol = 1e-09)

Arguments

x

A matrix with Euclidean data, continuous variables.

tol

A tolerance level to terminate the process. This is set to 1e-09 by default.

Details

The spatial median, using a fixed point iterative algorithm, for Euclidean data is calculated. It is a robust location estimate.

Value

A vector with the spatial median.

Author(s)

Manos Papadakis and Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Manos Papadakis <papadakm95@gmail.com>

References

Jyrki Mottonen, Klaus Nordhausen and Hannu Oja (2010). Asymptotic theory of the spatial median. In Nonparametrics and Robustness in Modern Statistical Inference and Time Series Analysis: A Festschrift in honor of Professor Jana Jureckova.

T. Karkkaminen and S. Ayramo (2005). On computation of spatial median for robust data mining. Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems, EUROGEN 2005, R. Schilling, W.Haase, J. Periaux, H. Baier, G. Bugeda (Eds) FLM, Munich. http://users.jyu.fi/~samiayr/pdf/ayramo_eurogen05.pdf

See Also

Examples

res<-spat.med( as.matrix( iris[, 1:4] ) )
res<-colMeans( as.matrix(iris[, 1:4]) )
res<-colMedians( as.matrix(iris[, 1:4]) )

Rfast

A Collection of Efficient and Extremely Fast R Functions

v2.0.1
GPL (>= 2.0)
Authors
Manos Papadakis, Michail Tsagris, Marios Dimitriadis, Stefanos Fafalios, Ioannis Tsamardinos, Matteo Fasiolo, Giorgos Borboudakis, John Burkardt, Changliang Zou, Kleanthi Lakiotaki and Christina Chatzipantsiou.
Initial release
2020-09-13

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