deepReg2d {DepthProc} | R Documentation |
Simple deepest regression method.
Description
This function calculates deepest regression estimator for simple regression.
Usage
deepReg2d(x, y)
Arguments
x |
Independent variable. |
y |
Dependent variable. |
Details
Function originates from an original algorithm proposed by Rousseeuw and Hubert. Let denotes a sample considered from a following semiparametric model:
, we calculate a depth of a fit
as
, where
denotes the regression residual,
,
.
The deepest regression estimator
is defined as
Author(s)
Daniel Kosiorowski, Mateusz Bocian, Anna Wegrzynkiewicz and Zygmunt Zawadzki from Cracow University of Economics.
References
Rousseeuw J.P., Hubert M. (1998), Regression Depth, Journal of The American Statistical Association, vol.94.
Examples
# EXAMPLE 1
data(pension)
plot(pension)
abline(
lm(Reserves ~ Income, data = pension),
lty = 3,
lwd = 2) # lm
abline(
deepReg2d(pension[, 1], pension[, 2]),
lwd = 2) # deepreg2d
# EXAMPLE 2
data(under5.mort)
data(inf.mort)
data(maesles.imm)
data2011 <- na.omit(
cbind(under5.mort[, 22], inf.mort[, 22],
maesles.imm[, 22]))
x <- data2011[, 3]
y <- data2011[, 2]
plot(
x, y,
cex = 1.2,
ylab = "infant mortality rate per 1000 live birth",
xlab = "against masles immunized percentage",
main = "Projection Depth Trimmed vs. LS regressions"
)
abline(lm(x ~ y), lwd = 2, col = "black") # lm
abline(
deepReg2d (x, y),
lwd = 2, col = "red"
) # trimmed reg
legend(
"bottomleft",
c("LS", "DeepReg"),
fill = c("black", "red"),
cex = 1.4,
bty = "n"
)
[Package DepthProc version 2.1.5 Index]