Sboot_loccov | R Documentation |
Calculates bootstrapped S-estimates using the Fast and Robust Bootstrap method.
Sboot_loccov(Y, R = 999, ests = Sest_loccov(Y))
Y |
matrix or data frame. |
R |
number of bootstrap samples. Default is |
ests |
original S-estimates as returned by |
This function is called by FRBpcaS
and FRBhotellingS
, it is typically not to be used on its own.
It requires the S-estimates of multivariate location and scatter/shape
(the result of Sest_loccov
applied on Y
), supplied through the argument ests
.
If ests
is not provided, Sest_loccov
calls the implementation of the multivariate S-estimates in package rrcov of Todorov and Filzmoser (2009) with default arguments.
For multivariate data the fast and robust bootstrap was developed by Salibian-Barrera, Van Aelst and Willems (2006).
The value centered
gives a matrix with R
columns and p+p*p
rows (p
is the number of variables in Y
),
containing the recalculated estimates of the S-location and -covariance. Each column represents a different bootstrap sample.
The first p
rows are the location estimates and the next p*p
rows are the covariance estimates (vectorized). The estimates
are centered by the original estimates, which are also returned through Sest
.
A list containing:
centered |
recalculated estimates of location and covariance (centered by original estimates) |
Sest |
original estimates of location and covariance |
Gert Willems, Ella Roelant and Stefan Van Aelst
M. Salibian-Barrera, S. Van Aelst and G. Willems (2006) PCA based on multivariate MM-estimators with fast and robust bootstrap. Journal of the American Statistical Association, 101, 1198–1211.
M. Salibian-Barrera, S. Van Aelst and G. Willems (2008) Fast and robust bootstrap. Statistical Methods and Applications, 17, 41–71.
V. Todorov and P. Filzmoser (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v032.i03")}.
S. Van Aelst and G. Willems (2013), Fast and robust bootstrap for multivariate inference: The R package FRB. Journal of Statistical Software, 53(3), 1–32. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v053.i03")}.
FRBpcaS
, FRBhotellingS
, MMboot_loccov
Y <- matrix(rnorm(50*5), ncol=5)
Sests <- Sest_loccov(Y, bdp = 0.25)
bootresult <- Sboot_loccov(Y, R = 1000, ests = Sests)
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