similar to: sometimes removing NAs from code

I have times and would like to round down to the earliest 30 minute increment. For instance, a time of 2011-04-28 09:02:00 (the as.numeric value = 1303999320) I would like it to be rounded down to: 2011-04-28 09:00:00 (the as.numeric value = 1303999200) Any ideas of how to do this? ----- In theory, practice and theory are the same. In practice, they are not - Albert Einstein -- View this

I have two more or less parallel dataframes that are giving me different results on one subset of variables. I know that I assembled the 2 dataframes slightly differently but I don't see why I am getting this result because one set of variables are labelled and the other is not. Variable names are the same, etc. as far as I can acertain. The only diffference seems to be that bdata variables

I have a new device that takes measurements anywhere from every second, to every 15 minutes (depending on changes). The matrix has a date, time and Y column (Y is the measurement). For three days it is 25,000 rows. How do I average the measurements by every 30 minutes so my matrix is 48 rows per day? I have been working on this and cannot figure out a simple method. Any ideas? Thank you. ----- In

I have a dataset where I have missing times (11:00 and 16:00). I would like the outputs to include the missing time so that the final time vector looks like "realt" and has the previous time's value. Ex. If meas at time 15:30 is 0.45, then the meas for time 16:00 will also be 0.45. meas are the measurements and times are the times at which they were taken. meas<-runif(18)

Dear R-list, I am in the process of translating a long function written in Matlab into R (mainly because I am a big of fan of R, and folks will not have to pay to use it :). In the translation of this function I got stack because they use spdiags, which, as far as I can tell it is not available in R. I have explored the Matrix package, from which I borrowed some of the functions (e.g.,

Hello! I work with : R : Copyright 2006, The R Foundation for Statistical Computing Version 2.3.1 (2006-06-01) On Windows XP Professional (Version 2002) SP2. At this moment I use the function "nls" combined with a selfStar model (SSmicmen, related to Michaelis-Menten equation, and provided by the "stats" package). When I realise the following operation (cf. p 59 of the

I would like to create a plot of y vs x with different treatments where the points are actually the letter of the treatment. Here is the code: A<-as.matrix(rnorm(10,10)) B<-as.matrix(rnorm(10,9.5)) C<-as.matrix(rnorm(10,10.5)) Y<-as.matrix(rnorm(30,13)) X<-rbind(A,B,C) nA<-matrix("A",10,1) nB<-matrix("B",10,1) nC<-matrix("C",10,1)

I have a combined date and time. I would like to separate them out into two columns so I can do things such as take the mean by time across all dates. meas<-runif(435) nTime<-seq(1303975800, 1304757000, 1800) nDateT<-as.POSIXct(nTime, origin="1970-01-01") mat1<-cbind(nDateT,meas) means1<- aggregate(mat1$meas, list(nDateT), mean) This doesn't do anything as each day

iterations <- 100 nvars <- 4 combined <- rbind(scaleMiceTrain, scaleMiceTest) reducedSample <- combined reducedSample <- subset(reducedSample, select = -pID50) reducedSample <- subset(reducedSample, select = -id) for (i in 1:iterations) { miceSample <- sample(combined[,-c(1,2)],nvars, replace=FALSE) miceSample$pID50 <- combined$pID50 miceTestSample <-

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

I am running the following nls equation. I tried it with data that excel was fitting and got the error: singular gradient matrix at initial parameter estimates I thought it was due to a low number of points (6), but when I create a dataset, I get the same problem. If I remove the parameter "a," then it can find a solution. Does anyone know what I can do to fit this model?

First thanks to the fast answer regarding the "Clustplot problem"... Regarding a new problem: for (i in 1:5) { z <- clara(adata, i) plot(z) } in the above code in the plot screen I get something like: clusplot(clara(x=adata,i)) in title in the 2nd type of plot I get silhouete plot of clara(x=adata,k=i,samples=50) How can I pass the real value to

I have brand new PC with this components: CPU Intel? Pentium G5400, LGA1151 motherboard ASUS PRIME B360M-C 16 GB RAM HDD 2x ADATA SSD 256GB XPG GAMMIX S11, PCIe Gen3x4 M.2 2280 (RAID1) NIC Intel X550-T1 Ethernet Converged Network Adapter I installed CentOS 7 and two NICs were detected: eno1 (on motherboard) enp1s0 (Intel X550-T1) When I restart the machine sometimes enp1s0 is missing. It is not

Dne 17.9.2019 v 15:25 Mauricio Tavares napsal(a): > On Tue, Sep 17, 2019 at 9:11 AM Miroslav Geisselreiter <mg at intar.cz> wrote: >> Dne 17.9.2019 v 14:02 Mauricio Tavares napsal(a): >>> On Tue, Sep 17, 2019 at 7:06 AM Miroslav Geisselreiter <mg at intar.cz> wrote: >>>> I have brand new PC with this components: >>>> CPU Intel? Pentium G5400,

Dne 17.9.2019 v 14:02 Mauricio Tavares napsal(a): > On Tue, Sep 17, 2019 at 7:06 AM Miroslav Geisselreiter <mg at intar.cz> wrote: >> I have brand new PC with this components: >> CPU Intel? Pentium G5400, LGA1151 >> motherboard ASUS PRIME B360M-C >> 16 GB RAM >> HDD 2x ADATA SSD 256GB XPG GAMMIX S11, PCIe Gen3x4 M.2 2280 (RAID1) >> NIC Intel X550-T1

If someone is able, can you tell me if there is a better way to do this? More specifically, do I have to rewrite all of the data members stuff and extend stuff of parent class in the child class? See below. Thanks in advance! Example 1: setConstructorS3("ClassA", function(A,x) { if(missing(A))A=15; if(missing(x))x=NA; extend(Object(), "ClassA", .size = A, .x=x

Hi, I have a gluster volume that consists of 22Bricks and includes a single folder with 3.6 Million files. Yesterday the volume crashed and turned out to be completely unresposible and I was forced to perform a hard reboot on all gluster servers because they were not able to execute a reboot command issued by the shell because they were that heavy overloaded. Each gluster server has 12 CPU cores

Full_Name: Barry Rowlingson Version: 2.2.0 OS: Linux Submission from: (NULL) (194.80.32.8) The image function with a matrix of all NA values fails with: > xyz=list(x=1:3,y=1:4,z=matrix(NA,3,4)) > image(xyz) Error in image.default(xyz) : invalid z limits In addition: Warning messages: 1: no finite arguments to min; returning Inf 2: no finite arguments to max; returning -Inf Image can

Hi I was using rsync with the following options rsync -aPH --exclude-from=/var/tmp/ignorelist /home/me/ /run/media/me/ADATA\ #2/rsync-me/ and I was creating a copy of a home directory on my Linux machine. It went along for sometime (some 30,000 files) when it stopped with the following message. ---> Desktop/OSme/Web-Site-Backups/backup-5.4.2014_15-11-43_linux014.tar.gz 4288446464 78%

On Tue, Sep 17, 2019 at 7:06 AM Miroslav Geisselreiter <mg at intar.cz> wrote: > > I have brand new PC with this components: > CPU Intel? Pentium G5400, LGA1151 > motherboard ASUS PRIME B360M-C > 16 GB RAM > HDD 2x ADATA SSD 256GB XPG GAMMIX S11, PCIe Gen3x4 M.2 2280 (RAID1) > NIC Intel X550-T1 Ethernet Converged Network Adapter > > I installed CentOS 7 and two