similar to: How do I sample "cases" within a matrix?

I have a data set like this in one .txt file (cols separated by !): APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! it contains over 14 000 000 records. Now

/etc/resolv.conf (Both DC's (windows) listed) domain ho-pla.se search ho-pla.se nameserver 10.0.2.10 nameserver 10.0.2.64 /etc/krb5.conf [libdefaults] dns_lookup_realm = false dns_lookup_kdc = true default_realm = HO-PLA.SE On Tue, Aug 6, 2024 at 9:01?PM Luis Peromarta via samba <samba at lists.samba.org> wrote: > > What?s the content of krb conf file and resolv.conf?

I'm having the most curious error while using the sem package. For the model I'm working with, I keep getting the following error: Error in J[cbind(1:n, observed)] <- 1 : subscript out of bounds I''ve used debug=TRUE with sem, and there don't appear to be any problems with model - there are no latent variables in this model. The variables in the covariance matrix

I'm looking over good-code a post-doc in my lab wrote and trying to learn how it works. I came across the following: rel.abundance <- as.matrix(read.delim("rel.abundance.csv",row.names=1,as.is =TRUE)) rel.abundance <- log2(rel.abundance-min(rel.abundance)+1) I'm not sure what the second line is doing. I ran each line in R and couldn't see a noticeable difference in

Hi all, I am fairly new to R and I am trying to run mvpart and create a MRT using explanatory variables and covariables. I've been following the procedures in Numerical Ecoogy with R. The command (no covariables) which works fine - ABUNDTMRT <- mvpart(abundance ~ .,factors,margin=0.08,cp=0,xv="1se",xval=nrow(abundance),xvmult=100,which=4) where abundance is 4th root

Hi fellow R users, I have a dataset that looks something like this. species class abundance K 1 592 K 2 288 G 1 254 G 2 239 C 2 173 D 2 123 E 3 89 F 2 87 B 2 86 H 2 82 I 1 79 J 2 76 B 1 73 D 3 72 A 2 62 L 2 58 I want to plot a stacked barchart. species is the x-axis, abundance is y-axis, and class will appear as the stacks in different colours. I need the species to be displayed in descending

Greetings, I am new to R and am hoping to get some tips from experienced R-programmers. I have a dataset that I've read into R as a dataframe. There are 5 columns: Plot location,species name, a species number code (unique to each species name), abundance, and treatment. There are 272 plots in each treatment, but only the plots in which the species was recorded have an abundance value. For

Hi there, I'm using the lattice package to create an xy plot of abundance vs. depth for 5 stages of barnacle larvae from 5 species. Each panel of the plot represents a different stage, while different loess smoothers within each panel should represent different species. However, I would like depth to be on the y-axis and abundance to be on the x-axis, because this is more intuitive as an

Hi guys, I'm very new to R and have been teaching myself over the past few months - it's a great tool and I'm hoping to use it to analyse my PhD data.As I'm a bit of a newb, I'd really appreciate any feedback and/or guidance with regards to the following questions that relate to generalized linearmixed modelling (or, at least, I think they do!)(if there is a 'better',

Hi. I am currently trying to run some Spearman correlations, and have encountered two issues. 1) When using cor.test() with a variable that includes ties, I get the "Cannot compute exact p-values with ties" error. I have read that this function now uses an asymptotic formula that allows for ties, so do not understand why I am getting this error. (I am running version 2.4.0.) I

I am using two mixed effect models. Firstly, what I am trying to do is to compare green roofs abundance with brownfield, green roof with green space abundance, and finally green space with brownfield abundance. I am unsure if I have done the correct model. I have to use a mixed effect model because my data is nested. This is the code and output >

Hello, please excuse the simplicity of this question as I am not very good with stats. I am taking a class, using R which I am learning at the same time, and the questions asks us to "Estimate the average abundance using Poisson regression with a log link". I can estimate the abundance from "x", but I can seem to figure out how to get the average abundance in this method. Any

Hi, I would like to calculate the RELATIVE euclidean distance. Is there a function in R which does it ? (I calculated the abundance of 94 chemical compounds in secretion of several individuals, and I would like to have the chemical distance between 2 individuals as expressed by the relative euclidean distance. Some compounds are in very low abundance whereas others are in high abundance,

Using platform x86_64-pc-linux-gnu arch x86_64 os linux-gnu system x86_64, linux-gnu status major 2 minor 13.0 year 2011 month 04

I have problem getting the concept of a nested fixed variable into the nlme scheme. I fear the question is very stupid. In the past I had asked this before, and never got a reply (in other cases, the response was within hours). I also checked the S-list, where several similar enquiries of other people are orphaned. We have a cross-over design, where patient are treated two weeks with placebo,

Dear list: I encountered some problems using the function point.in.polygon() of the sp package, when trying to determine whether some points lye inside, outside, on the border or on a vertice of a polygon. I have a list of point I know should lye right on the border of a polygon, but some of them are not classified as such by point.in.polygon() (see the example code below). To make a long story

I suppose that once you've got a 6502 working, adding support for a 4510 shouldn't be too difficult.... (http://c65gs.blogspot.com.au/) On Fri, Jul 4, 2014 at 10:38 AM, Bruce Hoult <bruce at hoult.org> wrote: > On Fri, Jul 4, 2014 at 12:02 PM, Edwin Amsler <edwinguy at gmail.com> wrote: > >> Well, the stack pointer be a single byte, so pushing things on there

Hello, I just realized that my second DC does not recognize the users from the AD. wbinfo -u/-g are working just fine. [root at dc1 ~]# id bruno.castro uid=10004(POL\bruno.castro) gid=100(users) grupos=100(users),10001(POL\ti),3000009(BUILTIN\users) [root at dc2 ~]# id bruno.castro id: bruno.castro: no such user [root at dc1 ~]# wbinfo -i bruno.castro POL\bruno.castro:*:10004:100:Bruno de

Could someone tell me how to access the log likelihood of a poisson model? I've done the following.... <BEGIN R STUFF> freq.mod <- glm(formula = nfix ~ gls.gls + pol.gls + pol.rel + rac.gls + rac.pol + rac.rac + rac.rel + white + gls.gls.w + pol.gls.w + pol.rel.w + rac.gls.w + rac.pol.w + rac.rac.w + rac.rac.w + rac.rel.w, family = poisson, data = Complex2.freq, offset = lnoffset)

hello, I am using following command classify_polarity(documents,algorithm="bayes",verbose=TRUE) output is: [1] "DOCUMENT 1" [1] "WORD: excited CAT: positive POL: strongsubj SCORE: 8.44419229853175" [1] "WORD: happy CAT: positive POL: strongsubj SCORE: 8.44419229853175" [1] "WORD: optimistic CAT: positive POL: weaksubj SCORE: 7.7510451179718" [1]