similar to: time series manipulation what functions are "best"

Another newbie question I got the 1 minute spine interpolation and 15 mean aggregation working with many thanks to Gabor Grothendieck using Zoo functions. I got a tip from Hasan Diwan to look at xts but it seemed I would make better progress using code from Gabor. Now I'm having trouble plotting this zoo object. I'm thinking I want a function to "split" the zoo object back to

Goal: get time series data interpolated on to desired time stamps. I have two or more data sets that have time stamps that vary from 5 mins to 3-5 hours. I want to get all the data put on common time stamps e.g. "00:05:00" intervals. I asked Gabor and got some very good code ( zoo aggregate, na.spline, na.approx) but I'm having trouble getting the csv file read in and converted to a

Hello, Please excuse me if this question has been asked before. I'm new to R, and have been trying to google the answers without any success. I would like to convert a set of date and time into R date-time class. Right now, the dates and times are in integer format, so I first need to convert them into string, and then to R date-time using strptime. However, I have a problem converting them

I have three columns in my raw data: date, time, and dry bulb temperature: http://r.789695.n4.nabble.com/file/n4495326/weathDataSDCoron.txt weathDataSDCoron.txt The date format is %Y%m%d and the time format is %H:%M. Any ideas on how to read it in such that it looks at the first two columns and then merges it into one column combining both the date and time? -- View this message in context:

It is not really a bug but a strange choice. When the option freq=F chosen, hist should plot relative frequency. It plots proportional to relative frequency by the factor of bin width. Is there a reason for this? A more normal choice seems to be to have it independent of the bin width. Yash Mittal University of Arizona ---------------------------------------------------------------- This

Hi all, I want to find all the mappings of one graph in another graph, based on their vertex labels Is there any way to do this in igraph based on vertex labels. (as far as i know Igraph allows the subgraph isomorphism based only on vertex and edge colors) Eg: graph 1: x(1) x(2) x(2) y(3) y(4) x(1) z(5) x(2) graph 2: x(1) y(2) # the brackets contain the corresponding vertex ids i would like my

platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor 7.1 year 2003 month 06 day 16 language R I have a Dell Inspiron 4000 laptop with Windows ME. I recently installed the 1.7 version of R. The following commands are from my

hello everyone, I'm wondering whether llvm can work together with simplescalar. Would anyone please give me some clarification? Thanks a lot!

hello everyone, I'm wondering whether llvm can work together with simplescalar. Would anyone please give me some clarification? Thanks a lot!

#I am trying to understand how R fits models for contrasts in a #simple one-way anova. This is an example, I am not stupid enough to want #to simultaneously apply all of these contrasts to real data. With a few #exceptions, the tests that I would compute by hand (or by other software) #will give the same t or F statistics. It is the contrast estimates that R produces #that I can't seem to

Dear Bert, thank you for your response. here it is the piece of R code : given 3 data frames below --- N <- data.frame(N=c("n1","n2","n3","n4")) M <- data.frame(M=c("m1","m2","m3","m4","m5")) C <- data.frame(n=c("n1","n2","n3"),

This email is also sent to cluster-devel at redhat.com. Since this issue is about both dlm and ocfs2, I send the email here to look for help from upstream. This is an already known issue. on ocfs2 with user space cluster stack, run the test script from http://people.redhat.com/~teigland/make_panic on the mounted ocfs2 volume from 2 nodes simultaneously, the access to ocfs2 volume on both nodes

Hi Bogdan, Kinda messy, but: N <- data.frame(N=c("n1","n2","n3","n4")) M <- data.frame(M=c("m1","m2","m3","m4","m5")) C <- data.frame(n=c("n1","n2","n3"), m=c("m1","m1","m3"), I=c(100,300,400))

> On Jun 6, 2017, at 4:01 AM, Jim Lemon <drjimlemon at gmail.com> wrote: > > Hi Bogdan, > Kinda messy, but: > > N <- data.frame(N=c("n1","n2","n3","n4")) > M <- data.frame(M=c("m1","m2","m3","m4","m5")) > C <-

I am trying to generate a fourth vector,z, given three known and fixed vectors, x1,x2,x3 with corresponding known and fixed correlations with themeselves and with z. That is, all correlations are known and prespecified. How can I do this? Thank you, ben

Hi all, I am new to LLVM (even the field of compiler) and currently I am engaged in the work of adapting LLVM IR to M5 simulator to observe the enhancement of the novel architecture we design. Simply speaking if you know little about M5, my aim is to know how LLVM IR is interpreted and encoded, then try to implement it in the framework of M5. I have read the LLVM documents, yet I still have some

Dear All, I am working with linear mixed-effects models using the lme4 package in R. I created a model with the lmer function including some main effects, a two-way interaction and a random effect. Now I am searching for a way to save the predicted values for this model. As far as I can see, there is no command in lme4 to save the predicted values (like the predict(model) function in e.g.

Hello all, Probably my concepts about the data.frame and matrix and array in R are not clear, I need some clarification to help me understand them better. >M <- read.table("test1.csv",sep=",",row.names=NULL,header=T) gives me: M as M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 1 9 11 14 15 18 20 20 20 20 20 2 3 4 8 9 11 12 14 15 15 15 3 4 5 8 8 9 9 9 9 9 9 4 4

Thank you for your answers and suggestions! Well, I want to do some experiments about the compiler optimization in llvm under SPM and I need performance evaluation. As I know, alpha is a general-purpose CPU, so I consider that arm may be an alternative. Simplesim-arm is able to do performance simulation while m5-arm is still under development. Then, what should I do? Do the experiment under

NB: This email and its contents are subject to the Eskom Holdings Limited EMAIL LEGAL NOTICE which can be viewed at http://www.eskom.co.za/email_legalnotice ------------------------------------------------------------------------ Good Morning Im busy doing an exercise on Foundation of Statistical Description and Analysis,Please check the attached exercise on page 3.In this exercise the first