Description Usage Arguments Details Author(s) References Examples
This function calculates deepest regression estimator for simple regression.
1 | deepReg2d(x, y)
|
x |
Independent variable. |
y |
Dependent variable. |
Function originates from an original algorithm proposed by Rousseeuw and Hubert. Let {Z} ^ {n} = {(x_1, y_1), ..., (x_n, y_n)} \subset {{R} ^ {d}} denotes a sample considered from a following semiparametric model: {{y}_{l}} = {{a}_{0}} + {{a}_{1}}{{x}_{1l}} + ... + {{a}_{(d - 1)l}}{{x}_{(d - 1)l}} + {{\varepsilon }_{l}}, {l = 1, ..., n} , we calculate a depth of a fit α = (a_{0}, ..., a_{d - 1}) as RD(α, {{Z} ^ {n}}) = {u \ne 0}\min\sharp {l: \frac{ {{r}_{l}}(α) }{ {{u} ^ {T}}{{x}_{l}} } < 0, l = 1, ..., n} , where r(\cdot) denotes the regression residual, α = (a_{0}, ..., a_{d - 1}) , {u} ^ {T}{x}_{l} \ne 0 . The deepest regression estimator
DR(α, {{Z} ^ {n}}) is defined as DR(α, {{Z} ^ {n}}) = {α \ne 0}\,\arg\max\,RD(α, {{Z} ^ {n}})
Daniel Kosiorowski, Mateusz Bocian, Anna Wegrzynkiewicz and Zygmunt Zawadzki from Cracow University of Economics.
Rousseeuw J.P., Hubert M. (1998), Regression Depth, Journal of The American Statistical Association, vol.94.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | # 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"
)
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