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...also hoping that this is in fact the right place to ask this question. I am very new to Samba and want to learn more. I have found several books available about Samba, but I don't know which one to get. So my question is... Which one is the book everyone figures is the best? Eric Johnson ejohnson@imagewireless.ca Wednesday, May 29, 2002 2:33 PM CST (-0600) --- Outgoing mail is certified Virus Free. Checked by AVG anti-virus system (http://www.grisoft.com). Version: 6.0.368 / Virus Database: 204 - Release Date: 29/05/2002

Thanks, but I am still having the same problem -- I made sure to reference the correct passwd file, but WinXP is still forcing me to logon as AGAMEMNON\Guest. Tim -----Original Message----- From: miles123@gmx.de [mailto:miles123@gmx.de] Sent: Monday, May 03, 2004 6:11 AM To: tbbooher@cox.net Subject: SOME Suggestions on [Samba] Can't the very basic stuff to work Hello Tim, I have read

I have a 3D scatterplot and would like to change the displayed range along the y-axis. for instance suppose I have: x = seq(0.2,0.7,0.01) y = seq(0.4,0.9,0.01) z = runif(51) scatterplot3d(x,y,z,xlim=c(0.2,0.7),ylim=c(0.4,0.9),zlim=c(0,1)) But would like the y-axis to read: 0.4, 0.5, 0.6, blank, blank, 1.0 Is there a way to issue an "axis" statement in the scatterplot3d? Also,

I am trying to do post-hoc tests associated with a repeated measures analysis with on factor nested within respondents. The factor (SOI) has 17 levels. The overall testing is working fine, but I can''t seem to get the multiple comparisons to work. The first step is to "stack" the data. Then I used "lme" to specify and test the overall model. Finally

I am using the package rpart to explore various classification structures. The call looks like: seekhi1<-rpart(pvol~spec+a1+psize+eppres+numpt+icds+bivalcrt+stents+ppshare+ nhosp+nyrs,data=dat,method="class", control=rpart.control(minsplit=30,xval=10)) The output is 1) root 198 87 1 (0.5606061 0.4393939) 2) psize=1,2 122 43 1 (0.6475410 0.3524590)

I am fitting a two dimensional smoother in gam, say junk = gam(y~s(x1,x2)), to a response variable y that is always positive and pretty well behaved, both x1 and x2 are contained within [0,1]. I then create a new dataset for prediction with values of (x1,x2) within the range of the original data. predict(junk,newdata,type="response") My predicted values are a bit strange