similar to: eigen() error: R Version 1.6.1 on Mac OS X (PR#2550)

I have a data frame (morgan) of hourly river flow, river levels and wind direction and speed thus: Time hour lev.morgan lev.lock2 lev.lock1 flow direction velocity 1 2009-07-06 15:00:00 15 3.266 3.274 3.240 1710.6 180.282 4.352 2 2009-07-06 16:00:00 16 3.268 3.272 3.240 1441.8 192.338 5.496 3 2009-07-06 17:00:00 17 3.268

Hello, We are having this issue with samba and OSX 10.2.3. We are using freebsd4.7 serving samba as a fileserver for our company, we have a mix of windows and macs connecting to it. The windows machines work just fine the macs are another story. I have narrowed it down to this: I can open a file/document from the fileserver on my mac and edit it but it tells me I dont have the permissions to

I would like to ude the function "qdagum", to compite quantiles of dagum distribution, but if I use the form: >qdagum(0.1, 4, 7206, 0.648) Error in qdagum(0.1, 4, 7206, 0.648) : object 'Scale' not found Error will apper, Could you help me? Thank you very much in advance, Alena -- View this message in context:

dear r-helpers i've got a table that in extracts looks like this: V1 V2 V3 V4 V5 1 01/01/1975 00:00:00 125.837 3.691 296.618 2 01/01/1975 01:00:00 124.799 3.679 281.307 3 01/01/1975 02:00:00 111.607 3.536 281.307 4 02/24/1976 11:00:00 21.602 2.555 93.893 5 02/24/1976 12:00:00 27.804 2.623 93.893 6 02/24/1976 13:00:00 26.105 2.604 114.716 7 10/18/1977

I have a file, each column of which is a separate year, and each row of each column is mean precipitation for that month. Looks like this (except it goes back to 1964). month X2000 X2001 X2002 X2003 X2004 X2005 X2006 X2007 X2008 X2009 1 1.600 1.010 4.320 2.110 0.925 3.275 3.460 0.675 1.315 2.920 2 2.960 3.905 3.230 2.380 2.720 1.880 2.430 1.380

Hi, I want to produce two parallel rotated strips with color gradient. So far, the sample strip is something produced by this: pushViewport(viewport(x = unit(0.638, "npc"), y =unit(0.386, "npc"), width=.62, height=0.006, angle=137.2)) grid.rect(y=100:1/100, just="top", gp=gpar(col=NA, fill=colorRampPalette(c("lightgray",

Hello all: I am confused about the output from a lm() model with an incomplete design/missing level. I have two categorical predictors and a continuous covariate (day) that I am using to model larval mass (l.mass): leaf.species has three levels - map, syc, and oak cond.time has two levels - 30 and 150. There are no response values for Map-150, so that entire, two-way, level is missing.

I have a mac osx 10.2.3 as a server, anyone unfamiliar with it, it uses admin as main user. root is still on the system. Admin is admin of the password server which is required to login to samba. therefore root can't be the one to join. yet admin doesn't have rights to modify smbpasswd. I know the smb.conf config should work. I have added the users and machines using smbpasswd

Hi, with small matrices eigen works as expected: > eigen(cbind(c(1,4),c(4,7)), only.values = TRUE) $values [1] 9 -1 $vectors NULL > eigen(cbind(c(1,4),c(4,7))) $values [1] 9 -1 $vectors [,1] [,2] [1,] 0.4472136 -0.8944272 [2,] 0.8944272 0.4472136 > eigen(cbind(c(1,-1),c(1,-1))) $values [1] -3.25177e-17+1.570092e-16i -3.25177e-17-1.570092e-16i $vectors

Hi all, I am trying to run a glm with mixed effects. My response variable is number of seedlings emerging; my fixed effects are the tree species and distance from the tree (in two classes - near and far).; my random effect is the individual tree itself (here called Plot). The command I've used is: mod <- glmer(number ~ Species + distance + offset(area) + (1|Plot), family = poisson)

Hi all, I have a dataframe of behavioral observations from 360 fish, each with 241 observation points(rows), which looks like this: > head(d) fish treatment tank trial video tid pid ang.chg abs.ac t len vel d2p x y 1 1 3 1 1 1 1 1 NA NA 0.0 0.000 NA NA 5.169 9.617 2

Dear R community members, I think I am asking a very simple question, but I really looked up in the faqs and manuals and found nothing helpful. I am trying to plot a data frame with the following structure (this is just a small extract): glo conc odor line series X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 1 0 AIR LN1 UP -0.488

Hi, I am quite new to R and trying to analyze the following data. I have 28 controls and 25 patients. I measured X values of 4 different locations (A,B,C,D) in the brain image of each subject. And X ranges from 0 to 1. I think "control or patient" is a between subject factor and location is a within subject factor. So, controls: 28 patients: 25 (unbalanced data set) respone measure:

More precisely what I've discovered is, at least in the cases of 2.2.8a and 3.0alpha22, when a 64-bit Samba is built with Sun's Forte compiler you'll end up with something incompatible with Mac OS 10.2.3. I always compile Samba myself with Sun's compiler to produce a 64-bit Samba. Well yesterday it came to my attention that Mac OS 10.2.x doesn't work with whats on my main

What's the difference between user "123" and "devries"? Based on the output here, they seem the same..? tleilax*CLI> tleilax*CLI> sip show users Username Secret Accountcode Def.Context ACL Forcerport 201 password 201 default No Yes 123

Hi All, I have been able to modify the x-axis to start at zero by adding xlow and xhigh parameters; that was pretty simple. I have been unable to find the location of the code that would turn off the information weighting of the box size (I have smaller randomized trials getting less weight than a much larger non-randomized trial). The function is forestplot() from rmeta. Thanks for any

In R 2.8.0 on Windows (tested both under ESS and under R Console in case there was an I/O issue) There is a bug in printing val <- matrix(list(NA_complex_,NA_complex_),1). > dput(val) structure(list(NA_complex_, NA_complex_), .Dim = 1:2) > print(val) [,1] [1,] [,2] [1,] Note that a large number of spaces are printed instead of NA. Compare the unproblematic real case:

# I have a question about how factanal is calculating the regression factor # scores based on an oblique rotation (promax) of the factors. # # As is explained in the help file, regression factor scores are # obtained as # # hat f = Lambda' Sigma^-1 x # # However, according to Harman's "Modern Factor Analysis" (e.g. second # edition, pp. 351-352) the formula is # # hat f = Phi

Can anyone help explain to me why the two codes below have different result? I thought I can use log(time)~. to replace log(time)~dist+climb+timef.I am using CVlm from DAAG package. I think nihills is preloaded with the package. Thanks in advance. > CVlm(df=nihills, form.lm=formula(log(time)~.),plotit="Observed",m=2)Analysis of Variance Table Response: log(time) Df Sum Sq

It looks just like the classical F-test for lack-of-fit, using estimate of `pure errors' from replicates, doesn't it? This should be in most applied regression books. The power (i.e., probability of finding lack-of-fit when it exists) of such tests will depend on the data. Andy > From: RenE J.V. Bertin > > Hello, > > I'd like to come back to this question I