search for: class3

...that rows are summed by a group based on a certain variable. I'm pretty sure rowsum() or rowsums() can do this but it's difficult for me to figure out how it will work for my data based on the examples I've read. My data are structured like this: Plot SizeClass Stems 12 Class3 1 12 Class4 3 17 Class3 5 17 Class4 2 I simply want to sum the size classes by plot and create a new data frame with a size class called "Class34" or with the SizeClass variable removed. I actually do have other size classes...

...= "character")) if(!isGeneric("name")) setGeneric("name", function(object) standardGeneric("name")) setMethod("name", "Class1", function(object) object@name) setClass("Class2", representation("Class1")) setClass("Class3", representation("Class2")) setClass("Class4", representation("Class3")) setClass("Class5", representation("Class4")) getClass("Class3") # as I expected Class3Def <- getClassDef("Class3", where = topenv(parent.frame()))...

i  want to print in the console and to have an excel file like this no_GWP                NbOfPolicyClass1[0-1000]     NbOfPolicyClass2[1000-3000]        NbOfPolicyClass3[> 3000] No_GWPMax=8    NbpolicyClass1=5                   NbpolicyClass2=4                            NbpolicyClass3 =3              i have do it like this:!!! data1 <- read.csv2("c:/Total1.csv",sep=",") > data2 <- read.csv2("c:/GWPMax1.csv",sep=",&q...

Hi, Please advice on what type of graph can be used to display the following data set. I have the following: Name Class a Class 1 a Class4 b Class2 b Class1 d Class3 d Class5 e Class4 e Class2 So each entry in name can belong to more than one class. I want to represent the data as to see where overlaps occur that is which names are in the same Class Name and also which names are unique to a Class. I tough a Venn Diagram woul...

...ty), n=sum(Density)) and that gives me results that look like this: ElevCat DataSource SizeClass avgDensity sdDensity n 1 Elev1 FIA Class1 38.67768 46.6673478 734.87598 2 Elev1 FIA Class2 27.34096 23.3232470 820.22879 3 Elev1 FIA Class3 15.38758 0.7088432 76.93790 4 Elev1 VTM Class1 66.37897 70.2050817 24958.49284 5 Elev1 VTM Class2 39.40786 34.9343269 11782.95152 6 Elev1 VTM Class3 21.17839 12.3487600 1461.30895 But, instead of "sum(Density)", I'd really l...

...;Policy.Number") > M2$GWP_Max <- as.numeric(as.character(M2$GWP_Max )) > class1 <- M2[M2[,25]>0 & M2[,25]<1000,] > (NbpolicyClass1 <- nrow(class1)) [1] 5 > class2 <- M2[M2[,25]>1000 & M2[,25]<3000,] > (NbpolicyClass2 <- nrow(class2)) [1] 3 > class3 <- M2[M2[,25]>3000,] > (NbpolicyClass3 <- nrow(class3)) [1] 4 can you help me ? thank you a lot!! [[alternative HTML version deleted]]

...;Policy.Number") > M2$GWP_Max <- as.numeric(as.character(M2$GWP_Max )) > class1 <- M2[M2[,25]>0 & M2[,25]<1000,] > (NbpolicyClass1 <- nrow(class1)) [1] 5 > class2 <- M2[M2[,25]>1000 & M2[,25]<3000,] > (NbpolicyClass2 <- nrow(class2)) [1] 3 > class3 <- M2[M2[,25]>3000,] > (NbpolicyClass3 <- nrow(class3)) [1] 4 can you help me ? thank you a lot!! [[alternative HTML version deleted]]

...n't appear. I think i have to change the number of level but i don't really know. Please can you help me? Class Levels: 1 2 3 4 5 coxph(formula = Surv(delai.etat, etat) ~ class, data = igr1) coef exp(coef) se(coef) z p class2 -0.093 0.911 0.245 -0.38 7.0e-01 class3 -0.749 0.473 0.286 -2.62 8.9e-03 class4 -0.600 0.549 0.343 -1.75 8.0e-02 class5 -0.874 0.417 0.197 -4.44 8.9e-06 Likelihood ratio test=24.9 on 4 df, p=5.28e-05 n=740 (1 observations deleted due to missing) Thanks for your help Bertrand

...omething pretty stupid, because I always get an error, even if it seems I am doing everything like the examples. My code is below. set.seed(123) plotdata2<-data.frame(x=rep((1:4),4), y=rep(0.1*(1:4),4), group=sample(factor(rep(1:4,rep(4,4)), labels=c('Class1', 'Class2', 'Class3', 'Class4')))) plotdata2 <- plotdata2[order(plotdata2[,'group']),] plot0<-ggplot() layer1<-layer(data=plotdata2, mapping=aes_string(x='x',y='y'),geom='point', stat='identity') scaleY<-scale_y_continuous() scaleX <- scale_x_continuo...

...) I'd like to run some simple regressions that look something like this: lm(length ~ elapsed) I'd like to do the regressions several times, split out by questionkey, student, class. What I've been doing is using a series of which's to create new data sets (e.g. class1, class2, class3, class4) and running the regressions (or whatever) against each of those new data sets. It seems that there should be better a way to do this. -- Jay Pfaffman pfaffman at relaxpc.com +1-415-821-7507 (H) +1-415-810-2238 (M) -.-.-.-.-.-.-.-.-.-.-.-.-.-...

...les and this forum on my 2 questions. Hope you guys can help me out! :-) Many thanks in advance! Cheers, Lars Q1: I imported a csv file with columnames subject and class. There are about 1000 different classes... It looks like this: subject1, class1 subject1, class2 subject2, class1 subject2, class3 ... subject999, class1 subject999, class2 Now I want to transform this in R into a table (with columnnames subject,class1,class2,...) like: subject1, yes, yes, no, ... subject2, yes, no, yes, ... ... Q2: I want to count the matching class patterns in the previous table (output: in a table with co...

...od for this because it is threshold independent. I obtained the AUC for the fit model output from the c score (c = 0.78). For the predicted values and independent data, for each level of the response I used the ROCR functions to get the AUC (i.e., probability y >= class1, y >= class2, y >= class3 etc) and plotted the ROC curves for each. The AUC values are all higher (AUC = 0.80 - 0.93) for the predicted values than what I got from the fit model in lrm. I am not sure whether I have misinterpreted the use of the AUC for ordinal models or whether the prediction results are actually bette...

I has several model objects that flow down like a tree: Class1 has_many Class2 Class2 has_many Class3 and so on. when are the child records actually created? If I do: c1 = Class1.find(:all) are the child objects (C2s below) created then or not until i do something like: c2s = c1.C2s while iterating through the c1s? If the form, that''s cool, no problem, but If I''ve got say...

Hello, I have a question concerning the R-function chisq.test. For example, I have some count data which can be categorized as follows class1: 15 observations class2: 0 observations class3: 3 observations class4: 4 observations I would like to test the hypothesis whether the population probabilities are all equal (=> Test for discrete uniform distribution) If you have a small sample size and therefore a sparse (1xr)-table, then assumptions for chisquare-goodness-of-fit test are...

...oad CA file /etc/dovecot/all.der: Success May 7 21:05:29 10.10.10.213 dovecot: imap-login: Can't load CA file /etc/dovecot/all.der: Success /etc/dovecot/all.der was generated by concatinating the following (all in der format) http://www.cacert.org/certs/root.der http://www.cacert.org/certs/class3.der http://crl.cacert.org/revoke.crl http://crl.cacert.org/class3-revoke.crl # dovecot --version 1.0.10 reiserfs filesystem # uname -a Linux mail.cacert.org 2.6.22-vs2.2.0.7-gentoo #1 SMP Mon May 5 20:21:30 EST 2008 x86_64 GNU/Linux # dovecot -n # 1.0.10: /etc/dovecot/dovecot.conf protocols: i...

My external node classifier returns some arrays in the list of parameters. Example output (names have been changed to protect the innocent): $ ./node_classifier a.b.com --- %YAML:1.0 "classes": ["class1", "class2", "class3"] "parameters": "hostname": "a" "name": "a" "domain": "b.com" "fqdn": "a.b.com" "group": "<host group>" "clusters": ["cluster1", "cluster2&qu...

...g #Subset the data by states PUFnum <- subset(PUF, state==num) #Attach data set with state specific data attach(PUFnum) #Run our prediction regression #the variables class1 through e19700 are the 27 covariates I want to use regression <- lapply(PUFnum, function(z) lm(z ~ class1+class2+class3+class4+class5+class6+class7+xtot+e00200+e00300+e00600+e00900+e01000+p04470+e04800+e09600+e07180+e07220+e07260+e06500+e10300+e59720+e11900+e18425+e18450+e18500+e19700)) Beta <- lapply(regression, function(d) d<- coef(regression$d)) detach(PUFnum) } Thanks, Mike [[alternative HTML version...

...I need a worker: QUEUE=<class> rake resque:work The problem with this solution is that it consumes a lot of memory. At the moment I have 30 different classes and it is still growing. Another solution is to let several classes share one queue like this: QUEUE=<class1>,<class2>,<class3> rake resque:work The problem with this is when a job of e.g. class1 hangs, jobs of class2 and class3 won''t run either. Exiting the job when it runs too long isn''t an option either, because I never know how long a normal job will run. So that''s why I''m coming...

Hi I share my bandwith (adsl 512/128) between 12 users. I set up simple qos script for incoming (IMQ) and outgoing traffic using htb in root, 4 classess and esfq qdisc at leafs. Interactive traffic goeas to class1 , http,mail etc. to class2, p2p, ftp to class3, and rest to class4. Classess divide link in proportion 20% (prio 1), 40% (prio 2), 20% (prio 3) ,20% (prio 4) This works very well when users surfing internet (www,mail, ssh), but is insufficient when i really need low, stable latency for example for games. Games traffic is in class1....

Hi, I run R 2.10.1 under ubuntu 10.04 LTS (Lucid Lynx) and klaR version 0.6-4. I compute a model over a 2 classes dataset (composed of 700 examples). To that aim, I use the function NaiveBayes provided in the package klaR. When I then use the prediction function : predict(my_model, new_data). I get the following warning : "In FUN(1:747[[747L]], ...) : Numerical 0 probability with