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Hi, I am trying to install samba on the RHEL. The installation completes but after that I get the smbd dead message upon checking the status: [root@usps-dc1-pc12 share]# [root@usps-dc1-pc12 share]# service smb status smbd dead but pid file exists nmbd (pid 8078) is running... [root@usps-dc1-pc12 share]# The version of RHEL and samba are as follows: [root@usps-dc1-pc12 samba]# cat /etc/redhat-release Red Hat Enterprise Linux Server rele...

...thing. The problem stays the same. I also took a machine from the domain, but cannot add it again. Windows gives me a "user unknown" reply when i do. The samba logs tell me this: [2008/06/04 17:49:13, 2] smbd/reply.c:reply_special(324) netbios connect: name1=OCTOPUS name2=CO114-PC12 [2008/06/04 17:49:13, 2] smbd/reply.c:reply_special(331) netbios connect: local=octopus remote=co114-pc12, name type = 0 [2008/06/04 17:49:13, 2] smbd/sesssetup.c:setup_new_vc_session(1209) setup_new_vc_session: New VC == 0, if NT4.x compatible we would close all old resources. [2008/06/04 17:4...

...974144 1.813919 1.416385 0.9981993Proportion of Variance 0.50054 0.212320 0.171060 0.04306 0.034740 0.012150 0.010260 0.006250 0.0031100Cumulative Proportion 0.50054 0.712870 0.883920 0.92698 0.961720 0.973870 0.984130 0.990380 0.9934900 PC10 PC11 PC12 PC13 PC14 PC15 PC16 PC17Standard deviation 0.9269088 0.8002766 0.4510176 0.3911732 0.3414279 0.2566597 0.2248179 6.359533e-16Proportion of Variance 0.0026800 0.0020000 0.0006300 0.0004800 0.0003600 0.0002100 0.0001600 0.000000e+00Cumulative Proportion 0.996...

Hey, I need some help. I want to obtain a cross validation for a regression model (binary response) but I got an error with CVbinary. Well I did this: fit <- lm(resp ~ PC1 + PC2 + PC3 + PC4 + PC5 + PC6 + PC7 + PC8 + PC9+PC10+PC11+PC12+PC13+PC14+PC15+PC16+PC17+PC18+PC19+PC20+PC21+PC22+PC23+PC24+PC25+PC26+PC27+PC28, data = dexp.cp, family=binomial()) CVbinary(fit) Error in sample(nfolds, m, replace = TRUE) : invalid 'size' argument I cannot understand this error, I was googling it, but i didn't find nothing really he...

...Standard deviation 3.6415 2.7178 1.8447 1.3943 1.10207 0.90922 0.76951 0.67490 Proportion of Variance 0.4352 0.2424 0.1117 0.0638 0.03986 0.02713 0.01943 0.01495 Cumulative Proportion 0.4352 0.6775 0.7892 0.8530 0.89288 0.92001 0.93944 0.95439 PC9 PC10 PC11 PC12 PC13 PC14 Standard deviation 0.60833 0.51638 0.49048 0.44452 0.40326 0.3904 Proportion of Variance 0.01214 0.00875 0.00789 0.00648 0.00534 0.0050 Cumulative Proportion 0.96653 0.97528 0.98318 0.98966 0.99500 1.0000 > which computes the *proportions* as if there were only 14 PCs in tot...

...76951 > > 0.67490 > > Proportion of Variance 0.4352 0.2424 0.1117 0.0638 0.03986 0.02713 > 0.01943 > > 0.01495 > > Cumulative Proportion 0.4352 0.6775 0.7892 0.8530 0.89288 0.92001 > 0.93944 > > 0.95439 > > PC9 PC10 PC11 PC12 PC13 PC14 > > Standard deviation 0.60833 0.51638 0.49048 0.44452 0.40326 0.3904 > > Proportion of Variance 0.01214 0.00875 0.00789 0.00648 0.00534 0.0050 > > Cumulative Proportion 0.96653 0.97528 0.98318 0.98966 0.99500 1.0000 > > > > > > > which com...

...on of Variance 0.4352 0.2424 0.1117 0.0638 0.03986 0.02713 >>> 0.01943 >>>> 0.01495 >>>> Cumulative Proportion 0.4352 0.6775 0.7892 0.8530 0.89288 0.92001 >>> 0.93944 >>>> 0.95439 >>>> PC9 PC10 PC11 PC12 PC13 PC14 >>>> Standard deviation 0.60833 0.51638 0.49048 0.44452 0.40326 0.3904 >>>> Proportion of Variance 0.01214 0.00875 0.00789 0.00648 0.00534 0.0050 >>>> Cumulative Proportion 0.96653 0.97528 0.98318 0.98966 0.99500 1.0000 >>>>> &...

...2.7178 1.8447 1.3943 1.10207 0.90922 0.76951 > 0.67490 > Proportion of Variance 0.4352 0.2424 0.1117 0.0638 0.03986 0.02713 0.01943 > 0.01495 > Cumulative Proportion 0.4352 0.6775 0.7892 0.8530 0.89288 0.92001 0.93944 > 0.95439 > PC9 PC10 PC11 PC12 PC13 PC14 > Standard deviation 0.60833 0.51638 0.49048 0.44452 0.40326 0.3904 > Proportion of Variance 0.01214 0.00875 0.00789 0.00648 0.00534 0.0050 > Cumulative Proportion 0.96653 0.97528 0.98318 0.98966 0.99500 1.0000 > > > > which computes the *proportions* as if...

...0 >>> Proportion of Variance 0.4352 0.2424 0.1117 0.0638 0.03986 0.02713 >> 0.01943 >>> 0.01495 >>> Cumulative Proportion 0.4352 0.6775 0.7892 0.8530 0.89288 0.92001 >> 0.93944 >>> 0.95439 >>> PC9 PC10 PC11 PC12 PC13 PC14 >>> Standard deviation 0.60833 0.51638 0.49048 0.44452 0.40326 0.3904 >>> Proportion of Variance 0.01214 0.00875 0.00789 0.00648 0.00534 0.0050 >>> Cumulative Proportion 0.96653 0.97528 0.98318 0.98966 0.99500 1.0000 >>>> >>> &gt...

....2424 0.1117 0.0638 0.03986 0.02713 >>>> 0.01943 >>>>> 0.01495 >>>>> Cumulative Proportion 0.4352 0.6775 0.7892 0.8530 0.89288 0.92001 >>>> 0.93944 >>>>> 0.95439 >>>>> PC9 PC10 PC11 PC12 PC13 PC14 >>>>> Standard deviation 0.60833 0.51638 0.49048 0.44452 0.40326 0.3904 >>>>> Proportion of Variance 0.01214 0.00875 0.00789 0.00648 0.00534 0.0050 >>>>> Cumulative Proportion 0.96653 0.97528 0.98318 0.98966 0.99500 1.0000 >>&gt...

Hi All: I am running prcomp on a very large array, roughly [500000, 3650]. The array itself is 16GB. I am running on a Unix machine and am running ?top? at the same time and am quite surprised to see that the application memory usage is 76GB. I have the ?tol? set very high (.8) so that it should only pull out a few components. I am surprised at this memory usage because prcomp uses the SVD

Hi All: I am running prcomp on a very large array, roughly [500000, 3650]. The array itself is 16GB. I am running on a Unix machine and am running ?top? at the same time and am quite surprised to see that the application memory usage is 76GB. I have the ?tol? set very high (.8) so that it should only pull out a few components. I am surprised at this memory usage because prcomp uses the SVD