MedianPolishM.ConstructMPst: Median polish multidimensional.

In STMedianPolish: Spatio-Temporal Median Polish

Description

An additive model for multidimensional array is fitted, using Tukey's median polish procedure.

Usage

## S3 method for class 'ConstructMPst'
MedianPolishM(data, eps, maxiter, na.rm, ...)

Arguments

data	class ConstructMPst.
eps	real number greater than 0, default 0.01. A tolerance for convergence: see Details
maxiter	the maximum number of iterations. Default 10.
na.rm	logical. If the data contains NA's. Default TRUE.
...	ignored.

Details

The model fitted is an additive, μ +α _{a} + β _{b} + ξ _{c} + τ _{t}, where μ is an overall mean, α_{a} is the a-th row effect, β_{b} is the effect b-th column effect, ξ_{c} is the c-th layer effect, τ _{t} is the t-th time effect. The algorithm works by alternately removing medians of every spatio - temporal dimensions, and continues until the proportional reduction in the sum of absolute residuals is less than eps or until there have been maxiter iterations. If na.rm is FALSE, the presence of any NA value in x will cause an error, otherwise NA values are ignored. MedianPolishM returns an object of class MedianPolishM (see below). There is a plotting method for this class, plot.MedianPolishM.

Value

An object of class medpolish with the following named components in a list:

residuals	the residuals.
overall	the fitted constant term.
effects	the fitted every space - time effects.
iter	number of iterations used in the range maxiter.

References

Martínez, W. A., Melo, C. E., & Melo, O. O. (2017). Median Polish Kriging for space–time analysis of precipitation Spatial Statistics, 19, 1-20. [link]

Hoaglin, D. C., Mosteller, F., & Tukey, J. W. (Eds.). (2011). Exploring data tables, trends, and shapes (Vol. 101). John Wiley & Sons.[link]

STMedianPolish documentation built on May 2, 2019, 10:14 a.m.