similar to: Discriminant Analysis- Apparent error rate

Thank you so much Rui! On Sun, Feb 4, 2018 at 12:20 AM, Rui Barradas <ruipbarradas at sapo.pt> wrote: > Hello, > > Please always cc the list. > > As for the question, I believe the following does it. > > a <- strsplit(mydata$ID, "[[:alpha:]]+") > b <- strsplit(mydata$ID, "[[:digit:]]+") > > a <- sapply(a, `[`, 1) > c <-

Hi all, I used bwplot in lattice to create a 6-panel boxplot grouped by a conditioning variable (param) that displays concentration (conc) in response to treatment (trtmnt). Here is the functional part of my code followed by my three questions: library(lattice); ww<-read.csv(file="c:/Rdata/lattice_boxplot_prep.csv",header=TRUE,sep=","); attach(ww);

Thank you so much Rui. 1. How do I export this table to excel file? I used this tbl1 <- table(Country, IDNum) tbl2=addmargins(tbl1) write.xlsx(tbl2,"tt1.xlsx"),sheetName="summary", row.names=FALSE) The above did not give me that table. 2. I want select those unique Ids that do have records in all countries. From the above data set, this ID

Hi all I ran a workload that reads & writes within 10 files each file is 256M, ie, (10 * 256M = 2.5GB total Dataset Size). I have set the ARC max size to 1 GB on etc/system file In the worse case, let us assume that the whole dataset is hot, meaning my workingset size= 2.5GB My SSD flash size = 8GB and being used for L2ARC No slog is used in the pool My File system record size = 8K ,

Hello forum, I want to do a test of independence with svychisq, but I get an error, then this my code: am18 <- read.spss("C:/Users/diana/Dropbox/Semestre 10/Tesis 10/Tesis Diana/AMcomuna18-29MAR2012.sav", use.value.labels=TRUE, max.value.labels=Inf, to.data.frame=TRUE) b<-matrix(c(am18$N6_MANZANA),ncol=1) c<-matrix(c(am18$PM1_1_PONDEMUESTRA),ncol=1)

Hello R people I now know how to run my discriminant analysis with the lda function in MASS: lda.alain=lda(Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, gr, CV = FALSE) and it works fine. But I am missing a test and cannot find any help on how to get it, if it exist. The "S" equivalent: discrim(structure(.Data = Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, class = "formula"), data = gr,

Hello I have a data set like below: plate.id well.id Group HYB rlt1 1 P1 A1 Control SKOV3hyb 0.190 2 P1 A2 Control SKOV3hyb 0.210 3 P1 A3 Control SKOV3hyb 0.205 4 P1 A4 Control SKOV3hyb 0.206 5 P1 A5 Control SKOV3hyb 0.184 385 P1 A1 ovca SKOV3hyb 0.184 386 P1 A2 ovca SKOV3hyb 0.229 387

Hi, I'm a newbie in R and don't much aobut all the modules and their capabilities, but I'm interested in solving a problem about a discriminant analysis done with SPSS tool. The thing is that I would like to make a discrimant analysis similar to the one done with SPSS, but I can't find the way to solve it. I've been playing with R and I can handle more or less my data,

Hello, Thanks for the reproducible example. See if the following does what you want. IDNum <- sub("^(\\d+).*", "\\1", mydata$ID) Country <- sub("^\\d+(.*)", "\\1", mydata$ID) tbl1 <- table(Country, IDNum) addmargins(tbl1) tbl2 <- xtabs(Y ~ Country + IDNum, mydata) addmargins(tbl2) Hope this helps, Rui Barradas On 2/3/2018 3:00 AM, Val

Sorry, I forgot to mention that I used the package "klaR". > > Dear all, I am trying to do a n-fold cross-validation for a > regularized discrimant function analysis using rda from the package > klaR. However, I have problems to predict the groups from the > test/validation sample. The exmaples of the R documantation and > some online webpage also do not work.

Hi All, I would like to make an invitation to make a collective package with all functions related to TABLES. I know that there are many packages with these functions, the original idea is collect all this functions and to make a single package, because is arduous for the user know all this functions broadcast in many packages. So, I think that the original packages can continue with its

R has amazing capabilities, but percentage tables are a weak spot IMHO. There's prop.table but that's rather unwieldly, especially for multiway tables. CrossTable by Marc Schwartz in the gregmisc library makes percentage tables a breeze but is limited to two-way tables. So I decided to try my own hand at writing an R-function that would make it easy to produce nicely formatted percentage

Can't seem to get the code below working. It gets stuck on line 24 inside the function hm; comments show the line in question. The function hm is called by sapply and is at the bottom of the code. Other stuff above line 24 works correctly including the first couple of lines of the function hm. Should I be using a different apply function or am I doing something wrong with xmlTreeParse ?

Em Mon, 3 Jun 2019 09:34:15 +0200 Christophe Leroy <christophe.leroy at c-s.fr> escreveu: > Le 30/05/2019 ? 01:23, Mauro Carvalho Chehab a ?crit?: > > Mostly due to x86 and acpi conversion, several documentation > > links are still pointing to the old file. Fix them. > > > > Signed-off-by: Mauro Carvalho Chehab <mchehab+samsung at kernel.org> > > ---

I'm trying to insert rows of a data.frame into a database table, or update where the key fields of a record already exist in the table. I've come up with a possible solution below, but would like to hear if anyone has a better solution. # The problem demonstrated: # Create a data.frame with test values library(RODBC) tbl <- data.frame( key1 = rep(1:3, each = 2), key2 =

Full_Name: Clay B Version: 2.5.0 (2007-04-23) OS: Solaris Nevada Build 55b Submission from: (NULL) (65.101.229.198) I find that running this script causes R to segfault reliably. However, running just for one system at a time (modifying the for loop updating iter to run just for a system at a time works). The system is a Sun W2100z with 12 GB of ram, and R segfaults using only around 360 MB of

> From: "Pavel S. Ruzankin" <ruzankin at math.nsc.ru> > Let us consider the current uniform sampling without replacement > algorithm. It resides in function do_sample in > https://svn.r-project.org/R/trunk/src/main/random.c > Its complexity is obviously O(n), where the sample is selected from > 1...n, since the algorithm has to create a vector of length n. So

I used screen scraping to extract some information and put it into a table called tbl. Now I want to modify the table a bit so the data can be more useful. Here's the code I used: library(XML) rm(list=ls()) url <- "http://webapp.montcopa.org/sherreal/salelist.asp?saledate=05/25/2011" tbl <-data.frame(readHTMLTable(url))[2:405, c(3,5,6,8,9)] names(tbl) <-

Hi all, I have the data set df with three varaibles, x1 x2 x3 1 2 5 2 4 1 5 6 0 1 1 2 I want to insert more rows ( eg, 3 rows with value filled with zeros) 1 2 5 2 4 1 5 6 6 1 1 2 0 0 0 0 0 0 0 0 0 Can any body help me out? Thanks

I was able to reproduce the problem with this self-contained example. Maybe it could be reproduced with an even smaller one ... library(tidyquant) # Loads tidyverse, tidyquant, financial pkgs, xts/zoo library(xts) dtV <- as.Date("2017-01-01") + 1:100 locL <- list( foo=xts(rnorm(100), order.by=dtV), bar=xts(rnorm(100), order.by=dtV) ) fullXts <- do.call(merge,locL) smallXts