ridgeSIR: ridge SIR

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/ridgeSIR.R

Description

ridgeSIR performs the first step of the method (ridge regularization of SIR)

Usage

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ridgeSIR(x, y, H, d, mu2 = NULL)

Arguments

x

explanatory variables (numeric matrix or data frame)

y

target variable (numeric vector)

H

number of slices (integer)

d

number of dimensions to be kept

mu2

ridge regularization parameter (numeric, positive)

Details

SI-SIR

Value

S3 object of class ridgeRes: a list consisting of

Author(s)

Victor Picheny, [email protected]

Remi Servien, [email protected]

Nathalie Villa-Vialaneix, [email protected]

References

Picheny, V., Servien, R. and Villa-Vialaneix, N. (2016) Interpretable sparse SIR for digitized functional data. Preprint.

See Also

sparseSIR, SISIR, tune.ridgeSIR

Examples

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set.seed(1140)
tsteps <- seq(0, 1, length = 50)
simulate_bm <- function() return(c(0, cumsum(rnorm(length(tsteps)-1, sd=1))))
x <- t(replicate(50, simulate_bm()))
beta <- cbind(sin(tsteps*3*pi/2), sin(tsteps*5*pi/2)) 
y <- log(abs(x %*% beta[ ,1])) + sqrt(abs(x %*% beta[ ,2]))
y <- y + rnorm(50, sd = 0.1)
res_ridge <- ridgeSIR(x, y, H = 10, d = 2, mu2 = 10^8)
## Not run: print(res_ridge)

SISIR documentation built on May 29, 2017, 8:31 p.m.