search for: pricip

Hi all, Does anyone know how to get the independent components and loadings from an Independent Component Analysis (ICA), as well as principal components and loadings from a Pricipal Component analysis (PCA) using the fastICA package? Or perhaps if there's another way to do ICAs in R? Below is an example from the fastICA manual (http://cran.r-project.org/web/packages/fastICA/fastICA.pdf) if(require(MASS)) { x <- mvrnorm(n = 1000, mu = c(0, 0), Sigma = matrix...

...his because i needed AES128-CTS-HMAC-SHA1-96 AES256-CTS-HMAC-SHA1-96 in my keytab of my new proxy. Is this normaly behaivor?   And can someone explain why the default keytabs have : arcfour-hmac aes256-cts-hmac-sha1-96 aes128-cts-hmac-sha1-96 des-cbc-md5 des-cbc-crc   and the exported with –pricipal only : arcfour-hmac des-cbc-md5 des-cbc-crc   Thanks in advance and when im done i’ll post the howto for this.     Best regards,   Louis    

...12e-05 -1.264 0.210 --- Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 Residual standard error: 0.691 on 68 degrees of freedom Multiple R-squared: 0.3644, Adjusted R-squared: 0.3364 F-statistic: 12.99 on 3 and 68 DF, p-value: 8.368e-07 x2,x3 is not significance. by pricipal, after PCA, the pcs should significance, but my data is not, why? -- View this message in context: http://old.nabble.com/after-PCA%2C-the-pc-values-are-so-large%2C-wrong--tp26240926p26240926.html Sent from the R help mailing list archive at Nabble.com.

Hi all. I have the following setup: 1st dc is on CentOS 6 with Sernet samba 4.1.13 2nd dc is on Debian 7 with Sernet samba 4.1.13 The 2 dc work as expected. on CentOS I was able to configure sssd to work on Debian I'm using winbind Now I have a 3rd server which is CentOS 7 with samba 4.1.1 from CentOS repository. This system serves as a file server and works ok with samba, but I have a

...e stored on glusterfs. 5) Fallback passwords for cloud access Concerning 1) and 2) I keep reading that this is possible, but I could not find any concise and current description. I'd welcome pointers to howtos. Concerning 3) this should be a matter of ACL, e.g. a single real user (kerberos pricipal) may have several mail-boxes (virtual users), and groups of real users may share the same mail-box. I have a faint idea, how this could be done in Cyrus (but never did that), but I read that these features should exist in Dovecot as well. But I'm completely lost to even figure out a start...

biplot could benefit from allowing colour palettes, eg. allowing col=list(xcol= xxpal, ycol= yypal) where xxpal and yypal are palettes. For an example, see the robust pricipal components in the principal componetent section of <http://www.statlab.uni-heidelberg.de/data/olive/olive10.pdf> The required change is to replace col[1L] resp. col[2L] by col[1L]] reep. col[[2L]] for example in plot(x, type = "n", xlim = xlim, ylim = ylim, col = col[[1L]], #...

...ance Vector Machines for regression o specc() : Spectral Clustering o kkmeans() : Kernel k-means clustering o ranking() : Kernel-based ranking method o onlearn() : Kernel-based Online Learning algorithms for classification, novelty detection and regression o kpca() : Kernel Pricipal Components Analysis o kcca() : Kernel Canonical Correlation Analysis o kfa() : Kernel Feature Analysis o sigest() : Hyperparameter estimation for the Gaussian and the Laplacian kernels o inchol() : Incomplete Cholesky decomposition method o csi() : Cholesky decomposition with side infor...

...ance Vector Machines for regression o specc() : Spectral Clustering o kkmeans() : Kernel k-means clustering o ranking() : Kernel-based ranking method o onlearn() : Kernel-based Online Learning algorithms for classification, novelty detection and regression o kpca() : Kernel Pricipal Components Analysis o kcca() : Kernel Canonical Correlation Analysis o kfa() : Kernel Feature Analysis o sigest() : Hyperparameter estimation for the Gaussian and the Laplacian kernels o inchol() : Incomplete Cholesky decomposition method o csi() : Cholesky decomposition with side infor...

I am measuring the performance of one TCP connection over two symmetric paths. Packets are sent to two paths alternatively. I found that when the latency of each path are within 1ms, the overall TCP throughput is the *sum* of the throughput of the two paths. However, when the latency of the two paths increases to 5ms, the overal TCP throughput drops to the throughput of a *single* path. Has anyone

https://bugzilla.mindrot.org/show_bug.cgi?id=2655 Bug ID: 2655 Summary: AuthorizedKeysCommand with large output can deadlock Product: Portable OpenSSH Version: 7.2p2 Hardware: All OS: Linux Status: NEW Severity: normal Priority: P5 Component: sshd Assignee: unassigned-bugs at

Dear R list, I'm trying to calculate Mahalanobis distances for 'Species' of 'iris' data as obtained below: Squared Distance to Species From Species: Setosa Versicolor Virginica Setosa 0 89.86419 179.38471 Versicolor 89.86419 0 17.20107 Virginica 179.38471 17.20107 0 These distances were obtained with proc 'CANDISC'