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/dports/math/R-cran-robustbase/robustbase/tests/
H A DMCD-specials.Rout.save56 $ raw.center: Named num 0.325
64 $ raw.cnp2 : num [1:2] 6.45 1.14
65 $ cnp2 : num [1:2] 1.47 1.01
128 $ raw.cnp2 : num [1:2] 1 1
129 $ cnp2 : num [1:2] 1.14 1
189 $ raw.center : Named num 1
200 $ raw.cnp2 : num [1:2] 4.97 1.41
201 $ cnp2 : num [1:2] 1 1
259 $ raw.center : Named num 1
267 $ raw.cnp2 : num [1:2] 1 1
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/dports/math/R-cran-robustbase/robustbase/man/
H A DltsReg.Rd107 returned also in the vectors \code{raw.cnp2} and \code{cnp2} of
134 i.e., the sum of the \eqn{h} smallest squared raw residuals.
141 the best subset found and used for computing the raw estimates, with
153 \item{cnp2}{a vector of length two containing the consistency
156 \item{raw.coefficients}{vector of raw coefficient estimates (including
158 \item{raw.scale}{scale estimate of the raw residuals.}
159 \item{raw.resid}{vector like \code{y} containing the raw residuals
161 \item{raw.cnp2}{a vector of length two containing the consistency
163 raw estimate of the error scale.}
169 \item{raw.weights}{
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H A DcovMcd.Rd19 covMcd(x, cor = FALSE, raw.only = FALSE,
30 \item{raw.only}{should only the \dQuote{raw} estimate be returned,
112 \code{raw.cnp2}.
118 Based on these raw MCD estimates, (unless argument \code{raw.only} is
128 \code{cnp2}. Details for the computation of the finite sample
155 \item{cnp2}{a vector of length two containing the consistency
158 \item{raw.center}{the raw (not reweighted) estimate of location.}
159 \item{raw.cov}{the raw (not reweighted) estimate of scatter.}
162 \item{raw.weights}{weights of the observations based on the raw
164 \item{raw.cnp2}{a vector of length two containing the consistency
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/dports/math/R-cran-robustbase/robustbase/vignettes/
H A DfastMcd-kmini.Rnw149 The raw MCD estimate of location, say $\hat{\mu}_0$, is then the average of these $h$ points,
150 whereas the raw MCD estimate of scatter, $\hat{\Sigma}_0$, is their covariance matrix,
155 %% \code{raw.cnp2}.
163 Based on these raw MCD estimates, $\bigl(\hat{\mu}_0, \hat{\Sigma}_0\bigr)$,
164 % (unless argument \code{raw.only} is true),
167 with respect to the scaled raw MCD, using the ``Mahalanobis''-like, robust distances
174 than the raw one, see \citet{PisGvAW02}.
177 \code{cnp2}. Details for the computation of the finite sample
/dports/math/R-cran-robustbase/robustbase/inst/doc/
H A DfastMcd-kmini.Rnw149 The raw MCD estimate of location, say $\hat{\mu}_0$, is then the average of these $h$ points,
150 whereas the raw MCD estimate of scatter, $\hat{\Sigma}_0$, is their covariance matrix,
155 %% \code{raw.cnp2}.
163 Based on these raw MCD estimates, $\bigl(\hat{\mu}_0, \hat{\Sigma}_0\bigr)$,
164 % (unless argument \code{raw.only} is true),
167 with respect to the scaled raw MCD, using the ``Mahalanobis''-like, robust distances
174 than the raw one, see \citet{PisGvAW02}.
177 \code{cnp2}. Details for the computation of the finite sample