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Dear all, I have two sets of data (say set1 and set2) as follow: set1 x1 x2 x3 0.30 0.43 3.88 0.38 0.59 3.53 0.30 0.42 2.12 0.33 0.53 2.12 0.30 0.47 3.76 set2 y1 y2 y3 0.32 0.47 5.18 0.23 0.26 1.06 0.42 0.65 3.88 0.28 0.38 3.76 0.35 0.47 1.41 The "pairs" function (such as pairs(~x1+x2+x3 data=set1, main="Simple Scatterplot Matrix") ) is

Dear R users, I am working on allocating the rows within a dataframe into some factor levels.Consider the following dataframe: Start.action Start.time 1 Start.setting 2010-12-30 17:58:00 2 Start.setting 2010-12-30 18:40:00 3 Start.setting 2010-12-31 22:39:00 4 Start.setting 2010-12-31 23:24:00 5

Dear R users, I'd like to change the default order of colors & line types. Especially I am using ggplot2 and using color Set1. In Set1, the default color order is red, blue, green, violet,.. ect. However, I want to put red in fourth (not first). Likewise, I want to change the order of default linetype. I want to put "solid" line in fourth. How can I do thses? R code to draw the

Good evening I often have as output from simulations a list of various values, vectors and matrices. Supposing that I then run said simulation several times, I often want to extract a particular result from each simulation for plotting and, ideally, put it in a matrix. A simple example v1 <- 1:5 v2 <- 6:10 other1 <- "stuff" other2 <- "stuff" set1 <-

Hello! I need to compare 2 datasets whether they come from the same distribution. I use function ks.boot{Matching}. And what is the confidence level of the p-value, returned by ks.boot function? The code is: set=read.table("http://stella.sai.msu.ru:8080/~gala/data/testsets.csv", header=T,sep=',') set1=set[!is.na(set$set1),'set1']

Colleagues, (R: 2.13.0; OS X) I often receive sequential datasets in which there are new rows interposed between existing rows. For example: SET1 <- data.frame(list(LETTERS=LETTERS[c(1:4, 6:10)], NUMBERS=c(1:4, 6:10))) SET2 <- data.frame(list(LETTERS=LETTERS[1:10], NUMBERS=1:10)) > SET1 LETTERS NUMBERS 1 A 1 2 B 2 3 C 3 4 D 4 5

Dear friends, I have a data set with 23 columns and 38000 rows. It is a panel running from the years 1991 through 2005. I want to aggregate the data and get the medians of each of the 23 columns for each of the years. In other words my output should be like this Year Median 1991 123 1992 145 1993 132 etc. The sample lines of code to do this operation is set1 <-

hi, I'm having rsync trouble I installt an new version of rsync on my server and clients (2.4.6) first every thing workt fine but now I'm having a lot of trouble. I use the following command to upload: rsync -vcrulpog -e ssh --delete --exclude=*lost+found --timeout=60 --password-file=/etc/rsyncpasswd /exports/set1/ user@1.2.3.4:/exports/set1/ and it gives me the following error:

Asterisk 1.4 r181990 given the dialplan snippet below, can anyone tell me why the h exten is not being run ? ============================================================================ console output: [Mar 29 10:33:49] -- Executing [s at questionnaire-menu:1] Set("Zap/1-1", "TIMEOUT(digit)=3") in new stack [Mar 29 10:33:49] -- Digit timeout set to 3 [Mar 29

Hi I am trying to use randomForest for classification. I am using this code: > set.seed(71) > rf.model <- randomForest(similarity ~ ., data=set1[1:100,], importance=TRUE, proximity=TRUE) Warning message: The response has five or fewer unique values. Are you sure you want to do regression? in: randomForest.default(m, y, ...) > rf.model Call: randomForest(x = similarity ~ .,

I have the following code for the minimum and maximum of my prediction interval > y.down=lines(x[x.order], set1.pred[,2][x.order], col=109) > y.up=lines(x[x.order], set1.pred[,3][x.order], col=109) domain=min(x):max(x) polygon(c(domain,rev(domain)),c(y.up,rev(y.down)),col=109) It doesnt seem to shade the right region, it gives me a trapezoid. Any help? Thanks!

I have encountered this problem on several occasions and am not sure how to handle it. I use for-loops to cycle through datasets. When each dataset is of equal length, it works fine as I can combine the datasets and have each loop pick up a different column, but when the datasets are differing lengths, I am struggling. Here is an example: A<-1:10 B<-1:15 C<-1:18

In http://lists.llvm.org/pipermail/cfe-commits/Week-of-Mon-20120827/063200.html, consecutive bitfields are wrapped as a group and represented as a large integer and emits loads stores and bit operations appropriate for extracting bits from within it. It fixes the problem of violating C++11 memory model that original widen load/store of bitfield was facing. It also brings more coalescing

Hello, I've been clustering my data using hclust and cutting the resulting tree with cutree. Separately, I visualize the clusterings with heatmap. Is it possible to have the dendrogram on the heatmap reflect the cutree results? That is, instead of having one large dendrogram, it would have 4 or 25 in the example below. Any guidance on if that's possible or not, and what kinds of

Hello, Please always cc the list. As for the question, yes, it does. If you want to remove just the ones with exactly 73.1 use the pattern grep("^73\\.1$", etc) Explanation: Beginning of string: ^ End of string: $ Escape special characters: \\ (needed because the period is a special character.) Hope this helps, Rui Barradas On 5/22/2018 12:50 PM, Ahmed Serag wrote: > Thank

I'm estimating two models for data with n = 179 with four clusters (21, 70, 36, and 52) named siteid. I'm estimating a logistic regression model with random intercept and another version with random intercept and random slope for one of the independent variables. fit.1 <- lmer(glaucoma~(1|siteid)+x1 +x2,family=binomial,data=set1,method="ML",

On 03/09/2017 12:28 PM, Krzysztof Parzyszek via llvm-dev wrote: > We could add intrinsics to extract/insert a bitfield, which would > simplify a lot of that bitwise logic. But then you need to teach a bunch of places about how to simply them, fold using bitwise logic and other things that reduce demanded bits into them, etc. This seems like a difficult tradeoff. -Hal > >

On Thu, Mar 9, 2017 at 10:54 AM, Hal Finkel <hfinkel at anl.gov> wrote: > On 03/09/2017 12:14 PM, Wei Mi via llvm-dev wrote: >> >> In >> http://lists.llvm.org/pipermail/cfe-commits/Week-of-Mon-20120827/063200.html, >> consecutive bitfields are wrapped as a group and represented as a >> large integer and emits loads stores and bit operations appropriate

Hi all, Suppose that I've two data frames, a and b say, both containing a column 'id'. While data frame 'a' contains multiple rows sharing the same id, data frame 'b' contains just one entry per id (i.e. a 1 to n relationship). For the ease of modeling I now want to generate a new data frame c, which is basically a copy of data frame 'a' augmented by the values

Hi, I am using ggplot2 to with the following code: gmathk2 <- qplot(time,math,colour=Kids,data=kids.ach.lm.k5,geom="smooth",method="lm",formula=y~ns(x,1)) + opts(title="Smoother Plot: Math K-5") + xlab("Time") + ylab("Math") + scale_colour_brewer(pal="Set1"); gmathk2 This plots all the smoother for all the x values. What I'd like