search for: cvmm

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2018 Mar 04
2
lmrob gives NA coefficients
...VNk=3 (0, ??), ?? the variance covariance matrix of errors, diag(??)= 1, off-diag(??)= ??= 0.15. To investigate the robustness of the estimators against outliers, we chosen different percentages of outliers ( 20%, 45%). We choose shrink parameter in (12) by minimize the new robust Cross Validation (CVMM) criterion which avoided 2018-03-04 0:52 GMT+01:00 David Winsemius <dwinsemius at comcast.net>: > > > On Mar 3, 2018, at 3:04 PM, Christien Kerbert < > christienkerbert at gmail.com> wrote: > > > > Dear list members, > > > > I want to perform an MM-...
2018 Mar 04
0
lmrob gives NA coefficients
...e variance covariance matrix of errors, diag(??)= 1, > off-diag(??)= ??= 0.15. To investigate the robustness of the estimators > against outliers, we chosen different percentages of outliers ( 20%, 45%). > We choose shrink parameter in (12) by minimize the new robust Cross > Validation (CVMM) criterion which avoided > > 2018-03-04 0:52 GMT+01:00 David Winsemius <dwinsemius at comcast.net>: > > > > > > On Mar 3, 2018, at 3:04 PM, Christien Kerbert < > > christienkerbert at gmail.com> wrote: > > > > > > Dear list members, > &...
2018 Mar 04
1
lmrob gives NA coefficients
...iance matrix of errors, diag(??)= 1, >> off-diag(??)= ??= 0.15. To investigate the robustness of the estimators >> against outliers, we chosen different percentages of outliers ( 20%, 45%). >> We choose shrink parameter in (12) by minimize the new robust Cross >> Validation (CVMM) criterion which avoided >> >> 2018-03-04 0:52 GMT+01:00 David Winsemius <dwinsemius at comcast.net>: >> >> > >> > > On Mar 3, 2018, at 3:04 PM, Christien Kerbert < >> > christienkerbert at gmail.com> wrote: >> > > >> &gt...
2018 Mar 04
0
lmrob gives NA coefficients
...??)= 1, >>> off-diag(??)= ??= 0.15. To investigate the robustness of the estimators >>> against outliers, we chosen different percentages of outliers ( 20%, >>> 45%). >>> We choose shrink parameter in (12) by minimize the new robust Cross >>> Validation (CVMM) criterion which avoided >>> >>> 2018-03-04 0:52 GMT+01:00 David Winsemius <dwinsemius at comcast.net>: >>> >>> > >>> > > On Mar 3, 2018, at 3:04 PM, Christien Kerbert < >>> > christienkerbert at gmail.com> wrote: >&gt...
2018 Mar 03
0
lmrob gives NA coefficients
> On Mar 3, 2018, at 3:04 PM, Christien Kerbert <christienkerbert at gmail.com> wrote: > > Dear list members, > > I want to perform an MM-regression. This seems an easy task using the > function lmrob(), however, this function provides me with NA coefficients. > My data generating process is as follows: > > rho <- 0.15 # low interdependency > Sigma <-
2018 Mar 03
2
lmrob gives NA coefficients
Dear list members, I want to perform an MM-regression. This seems an easy task using the function lmrob(), however, this function provides me with NA coefficients. My data generating process is as follows: rho <- 0.15 # low interdependency Sigma <- matrix(rho, d, d); diag(Sigma) <- 1 x.clean <- mvrnorm(n, rep(0,d), Sigma) beta <- c(1.0, 2.0, 3.0, 4.0) error <- rnorm(n = n,