spatmed.reg: Spatial median regression
In Rfast: A Collection of Efficient and Extremely Fast R Functions
View source: R/regression_models.R
Spatial median regression R Documentation
Spatial median regression
Description
Spatial median regression with Euclidean data.
Usage
spatmed.reg(y, x, tol = 1e-07)
Arguments
y
A matrix with the response variable.
x
The predictor variable(s), they have to be continuous.
tol
The threshold upon which to stop the iterations of the Newton-Rapshon algorithm.
Details
The objective function is the minimization of the sum of the absolute residuals.
It is the multivariate generalisation of the median regression.
Value
A list including:
iters
The number of iterations that were required.
be
The beta coefficients.
Author(s)
Michail Tsagris
R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr>
References
Biman Chakraborty (2003) On multivariate quantile regression. Journal of Statistical
Planning and Inference http://www.stat.nus.edu.sg/export/sites/dsap/research/documents/tr01_2000.pdf
See Also
spat.med, sscov, lmfit
Examples
x <- as.matrix(iris[, 3:4])
y <- as.matrix(iris[, 1:2])
mod1 <- spatmed.reg(y, x)
Rfast documentation built on Nov. 9, 2023, 5:06 p.m.
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View source: R/regression_models.R
| Spatial median regression | R Documentation |
Spatial median regression
Description
Spatial median regression with Euclidean data.
Usage
spatmed.reg(y, x, tol = 1e-07)
Arguments
y |
A matrix with the response variable. |
x |
The predictor variable(s), they have to be continuous. |
tol |
The threshold upon which to stop the iterations of the Newton-Rapshon algorithm. |
Details
The objective function is the minimization of the sum of the absolute residuals. It is the multivariate generalisation of the median regression.
Value
A list including:
iters |
The number of iterations that were required. |
be |
The beta coefficients. |
Author(s)
Michail Tsagris
R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr>
References
Biman Chakraborty (2003) On multivariate quantile regression. Journal of Statistical Planning and Inference http://www.stat.nus.edu.sg/export/sites/dsap/research/documents/tr01_2000.pdf
See Also
spat.med, sscov, lmfit
Examples
x <- as.matrix(iris[, 3:4])
y <- as.matrix(iris[, 1:2])
mod1 <- spatmed.reg(y, x)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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