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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 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

Sometimes I have NA values within specific columns of a dataframe (in this example, the first two columns can have NAs). If there are NA values, I would like them to be removed. I have been using the code: y<-c(NA,5,4,2,5,6,NA) z<-c(NA,3,4,NA,1,3,7) x<-1:7 adata<-data.frame(y,z,x) adata<-adata[-which(apply(adata[,1:2],1,function(x)any(is.na(x)))),] This works well if there are NA

I am trying to do a power analysis to get the number of replicas per treatment. If I try to get the power it works just fine: setn=c(2,3) sdx=c(1.19,4.35) power.t.test(n = setn, delta = 13.5, sd = sdx, sig.level = 0.05,power = NULL) If I go the other way to obtain the "n" I have problems. sdx=c(1.19,4.35) pow=c(.8,.8) power.t.test(n = NULL, delta = 13.5, sd = sdx, sig.level = 0.05,

I have a matrix where one column has a date and another column has a time. I need to delete all times before 6am. I had combined the Date and Time column into DateTime. Mat1: Weight Date Time 7.6 04/28/11 09:03 8.4 04/29/11 03:11 8.6 04/29/11 05:32 8.6 04/29/11 09:53 1.4 05/01/11 19:52 I tried just picking up the time: as.POSIXct(Mat1$Time, format = "%H:%M") but

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)

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 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)

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

I am plotting 28 plots on one screen: par(mfrow=c(4,7)) for (i in 1:28) { a<-seq(1,3,1) plot(a,a, ann=FALSE) } I want a main title for all the plots (I tried using main but that doesn't work). I deleted the axes, but am not sure how to delete the space. There are such large margins between plots so the plots themselves are very small. If I delete the margins I can leave them all on one

Totally and completely on my HP microfiber. Wouldn't get past anything to even get me into the grub menu. NOT AMUSED! _______________________ Kay Schenk

Hi - We have had 3 rather major occurances of ext3 filesystem corruption lately, i.e. so bad we couldn't event mount, and fsck didn't help. I am looking for pointers, that could help us investigate the root cause. In general... We are running RedHat WS 3 Update 6, 2.4.21-40.2.ELsmp or 2.4.21-37.ELsmp We have a small SAN system that looks like this

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?

dev.new(width=6, height=1.5,mar=c(0,0,0,0)) par(mfrow=c(1,1),mar=c(.5, .5, 1.5, .5), oma=c(.4, 0,.5, 0)) barplot(c(1,1,1,1,1,1),col=c("blue","purple","red","green","orange","yellow"), axes = FALSE) I have a barplot that returns six colors in a line. I would like to get the same six color blocks in a hexagram layout (if it were a clock,

And for whatever reason, both my centos 7 and 8 survived this apparently with flying colors. Actually, this is out of character for how fate has been dealing the cards recently. I'm very leary about rebooting either, now, though. On Sat, Aug 1, 2020 at 12:50 PM Kay Schenk <kay.schenk at gmail.com> wrote: > Totally and completely on my HP microfiber. Wouldn't get past

Here is the code I am running: library(nls2) modeltest<- function(A,mu,l,b,thour){ out<-vector(length=length(thour)) for (i in 1:length(thour)) { out[i]<-b+A/(1+exp(4*mu/A*(l-thour[i])+2)) } return(out) } A=1.3 mu=.22 l = 15 b = .07 thour = 1:25 Yvals<-modeltest(A,mu,l,b,thour)-.125+runif(25)/4 st2 <- expand.grid(A = seq(0.1, 1.6,.5), mu = seq(0.01, .41,.1), l=1, b =seq(0,.6,.3))