search for: pc4

Hi, I'm running Samba/openLDAP on a FC4 and I'm trying to make it work as a PDC. I installed all the software using yum instead smbldap-tools. I've done all the configuration but, when I try to join a Windows XP Professional named 'pc4' to the domain it fails with "Error joining the domain OPENWIRED. Username not found". And no machine account is created under ou=Computers,dc=openwired,dc=net If I run /usr/local/sbin/smbldap-useradd -w 'pc4$' it works OK. smbd.log at the end. When I start SAMBA it binds...

...fferent. First, I list my results from R,S-PLUS and SAS/STATA/SPSS, and then show the original dataset, hoping sb. to try and explain it. SAS,STATA,and SPSS have the same results, so i put them together. From their results, we see that the absolute values of coeffiecient are same, but PC1,PC2,PC4,PC5 and PC6 in R have the opposite sign on the coeffiecnts contrast with SAS, and PC4,PC5 in S-PLUS have the opposite sign on the coeffiecnts contrast with SAS. Curiously, I got the same results amont all these software using my another dataset. *R's results of PCA:* *PC1* *PC2*...

...om other data.frames. Something like: a b c d e f g v1 # # # # # # # v2 # # # # # # # v3 # # # # # # # v4 # # # # # # # v5 # # # # # # # v6 # # # # # # # I want to give the following column names to each data.frame: ("SDev", "PC1", "PC2", "PC3", "PC4", "PC5", "PC6") Works fine for one data.frame: column_names <- c("SDev", "PC1", "PC2", "PC3", "PC4", "PC5", "PC6") names( df1 ) <- column_names How is it to be done at once for all data.frames tha...

...mp' object whose components are some 'lists'. the second component is a list that comtains the following: > mylist <- churn[2] > class(mylist) [1] "list" > mylist PC1 PC2 PC3 PC4 PC5 PC6 Account_Length -8.930570e-03 2.383719e-03 -2.414908e-02 -1.004704e-01 9.941468e-01 2.867606e-02 Area_Code 1.543767e-02 -1.710566e-02 -6.258129e-03 9.945271e-01 1.008478e-01 -8.890155e-03 Intl_Plan...

...ngs between insect and soils data. Due to the corlinearity among predictors, I conducted principal component analysis and obtained first 4 principal components accounting over 85 % total variation. Using coefficient of 4 principal components, new 4 predictors were obtained as follows (i.e., PC1 ~ PC4); > head(df.chf09) chafer year longitude latitude paddock2 PC1 PC2 PC3 PC4 12152 0 2009 -87.85045 33.90220 11 1.1790748 -2.895178 -1.522787 -2.33674507 12153 0 2009 -87.85045 33.90214 11 0.7852655 -3.758568 -1.691573 -2.16018891 12154 0 2009...

Hello I am creating a linear model with the command net5 = lm( X[,1] ~ PrinComp[,1:5]) where my vector PrinComp looks like this > head(PrinComp[,1:5]) PC1 PC2 PC3 PC4 PC5 [1,] 1.8626055 -3.34190998 -0.5448889 2.8296751 0.3994096 [2,] 3.1124144 -1.68113572 1.7187314 -2.0162583 -0.2935675 [3,] 3.3538049 -0.05471002 -2.9385065 0.6921495 -2.2743761 [4,] 2.3491111 1.46433537 3.2600091 0.5121311 -2.2212727 [5,] 1.4467501 2.64829347 -2.4559811 -2.4745585...

...$fcst $PC1 fcst lower upper CI PC1.fcst 2.284497 -0.8033048 5.3723 3.087802 $PC2 fcst lower upper CI PC2.fcst -0.938333 -4.346927 2.470261 3.408594 $PC3 fcst lower upper CI PC3.fcst -1.035569 -4.282719 2.211582 3.247151 $PC4 fcst lower upper CI PC4.fcst -0.7063035 -4.027811 2.615204 3.321507 $PC5 fcst lower upper CI PC5.fcst 0.3664593 -1.689041 2.421959 2.055500 I would like to take the fcst object from each of the list elements and assign it to a vector, do you...

...coefficients. "lm(y~x)$coefficients" gives you just the regression coefficients when you carry out the command. When I carry out PCA on R, typically I get: Standard deviations: [1] 83.732400 14.212402 6.489426 2.4827900 Rotation: PC1 PC2 PC3 PC4 Murder 0.04170432 -0.04482166 0.07989066 -0.99492173 Assault 0.99522128 -0.05876003 -0.06756974 0.03893830 UrbanPop 0.04633575 0.97685748 -0.20054629 -0.05816914 Rape 0.07515550 0.20071807 0.97408059 0.07232502 I want to get only: PC1 PC2 PC3...

Dear All, when I'm running a PCA with prcomp(USArrests, scale = TRUE) I get the right principal components, but with the wrong sign infront Rotation: PC1 PC2 PC3 PC4 Murder 0.5358995 -0.4181809 0.3412327 0.64922780 Assault 0.5831836 -0.1879856 0.2681484 -0.74340748 UrbanPop 0.2781909 0.8728062 0.3780158 0.13387773 Rape 0.5434321 0.1673186 -0.8177779 0.08902432 instead of PC1 PC2 PC3 PC4 Murder -0.5358995 0.4181809 -0.3412327 0.64922780 Assault -0.5831836 0.18...

...of the swap curve. I want to put these probabilities in my dataframe mydata(given after the prob table). Prob of States Changes State1 State2 State3 State4 a Pa1 Pa2 Pa3 Pa4 b Pb1 Pb2 Pb3 Pb4 c Pc1 Pc2 Pc3 Pc4 d Pd1 Pd2 Pd3 Pd4 and I have a dataframe(with 93 rows) called mydata part of which(6 rows) is given below where I want to fill in the last four columns with probabilities taken from States.Prob according to the change and state in mydata4:- Change State PState1 PState2...

Hi everyone, I am doing PCA with labdsv package. I was trying to create a biplot graphs in order to observe arrows related to my variables. However when I run the script for this graph, the console just keep saying: *Error in nrow(y) : element 1 is empty; the part of the args list of 'dim' being evaluated was: (x)* could please someone tell me what this means? what i am doing

Hi, Suppose I have the following data frame. __BEGIN__ > library(MASS) > data(crabs) > crab.pca <- prcomp(crabs[,4:8],retx=TRUE) > crab.pca$rotation PC1 PC2 PC3 PC4 PC5 FL 0.2889810 0.3232500 -0.5071698 0.7342907 0.1248816 RW 0.1972824 0.8647159 0.4141356 -0.1483092 -0.1408623 CL 0.5993986 -0.1982263 -0.1753299 -0.1435941 -0.7416656 CW 0.6616550 -0.2879790 0.4913755 0.1256282 0.4712202 BD 0.2837317 0.1598447 -0.5468821 -0.6343657 0.4386868 __...

An embedded and charset-unspecified text was scrubbed... Name: not available URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20091122/6a079ab8/attachment-0001.pl>

Dear friends, what is this error message in gam???? I cannot understand what it means .... is it a bug? gam_bray_scot24_pc_0505<gam(bray~s(PC1,PC2,PC3,PC4,PC5, PC1.1,PC2.1,PC3.1,PC4.1,PC5.1),data=dist_scot24_vector_with_climate) Error in if (length(data) != vl) { : missing value where TRUE/FALSE needed Calls: gam ... smooth.construct -> smooth.construct.tp.smooth.spec -> array In addition: Warning message: In array(0, n * k) : NAs introduced...

...CA) num [1:922, 1:5] -0.0226 -0.0504 -0.0208 -0.0582 -0.0257 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:922] "abdomen.2" "abdomimal.3" "abdominal.4" "aberration.5" ... ..$ : chr [1:5] "PC1" "PC2" "PC3" "PC4" ... I want to order it according to PC1. I tried this dfCorTFandPCA=as.data.frame(corTFandPCA) > orderedCorTFandPCA=dfCorTFandPCA[order(PC1)] Error in order(PC1) : object 'PC1' not found but get that error. Can someone tell me what the best way to do this is? Thank you. -- Vi...

Hello again, I was hoping one of you could help me with this problem. Consider the sample data from R: > summary(prcomp(USArrests)) Importance of components: PC1 PC2 PC3 PC4 Standard deviation 83.732 14.2124 6.4894 2.48279 Proportion of Variance 0.966 0.0278 0.0058 0.00085 Cumulative Proportion 0.966 0.9933 0.9991 1.00000 How do I access the information contained within this summary? For instance, let's say I wanted to make a graph based on the second row...

...set), to a reduced number of components, i can evaluate % of variance explained, or am I missing something?? 8 variables in the data set > princ = prcomp(df[,-1],rotate="varimax",scale=TRUE) > summary(princ) Importance of components: PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 Standard deviation 1.381 1.247 1.211 0.994 0.927 0.764 0.6708 0.4366 Proportion of Variance 0.238 0.194 0.183 0.124 0.107 0.073 0.0562 0.0238 Cumulative Proportion 0.238 0.433 0.616 0.740 0.847 0.920 0.9762 *1.0000* > princ = prcomp(df[,-1],rotate="varimax&q...

...mpare the results obtained. Surprisingly, I do not obtain the same results for the coordinates of the principal composantes with these two softwares. using USArrests data I obtain with R : > summary(prcomp(USArrests)) Importance of components: PC1 PC2 PC3 PC4 Standard deviation 83.732 14.2124 6.4894 2.48279 Proportion of Variance 0.966 0.0278 0.0058 0.00085 Cumulative Proportion 0.966 0.9933 0.9991 1.00000 And using SPAD (french editor CISIA) : Ex: sd pv cp comp1 | 2.4802 | 62.01 | 62.01 | comp2 | 0.98...

...5.1 18 verginica now I used 'prcomp' function on dataset and got result as following: >print(pc) Standard deviations (1, .., p=4): [1] 1.7083611 0.9560494 0.3830886 0.1439265 Rotation (n x k) = (4 x 4): PC1 PC2 PC3 PC4 Sepal.Length 0.5210659 -0.37741762 0.7195664 0.2612863 Sepal.Width -0.2693474 -0.92329566 -0.2443818 -0.1235096 Petal.Length 0.5804131 -0.02449161 -0.1421264 -0.8014492 Petal.Width 0.5648565 -0.06694199 -0.6342727 0.5235971 I'm planning to use PCA as feature selection process and remov...

...-1.539887e-12 9.866600e-01 avg.EDGE.IN.SHORTEST.PATH.COUNT -6.976740e-01 2.413866e-16 -1.151131e-01 avg.EDGE.IN.SHORTEST.PATH.COUNT.1 -6.976740e-01 2.013413e-17 -1.151131e-01 avg.DEGREE 2.505027e-13 -1.000000e+00 -1.519375e-12 PC4 sum.delivery.penalty -1.118300e-17 avg.EDGE.IN.SHORTEST.PATH.COUNT 7.071068e-01 avg.EDGE.IN.SHORTEST.PATH.COUNT.1 -7.071068e-01 avg.DEGREE -3.253830e-18 > summary(pc2) Importance of components: PC1 PC2 PC3 PC4 Standard devi...