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Hi How would I analyse time series with - different lengths (i.e. one has 9 entries and the other has 14 entries) - different frequency (i.e. dates are random - no repeated length) - multiple values for the same time entry (e.g. 2009-10-23 below) i.e. my data takes the form: 1st time series 2009-10-07 0.009378 2009-10-19 0.014790 2009-10-23 -0.005946 2009-10-23 0.009096 2009-11-08 0.004189

Hello, I have some data that will be in the form: structure(list(station = structure(c(20L, 2L, 4L, 19L, 3L, 11L, 1L, 5L, 10L, 12L, 17L, 18L, 6L, 9L, 13L, 16L, 7L, 8L, 15L, 14L ), .Label = c("1", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "2", "3",

Hi all, I am trying to merge several data sets and end up with a long data format by date & time so I can run correlations and plots. I am using Deducer as an R GUI but can just use the R console if easier. The data sets are weather with wind speed, relative humidity and temperatures by date and minute and bat activity with date, time, label, and an activity index number. The bat

Dear All, 1.I have been trying to aggregate my data but I have not been getting it correctly. In the data I want to convert hourly data into daily averages. Here is a sample of the data: Neph_no Date Time Temp_C Pressure_kPa RH 9 2014/03/28 10:00:00 38.4 95.9 29.7 9 2014/03/28 11:00:00 37.8 95.8 29.2 9 2014/03/28 12:00:00 36.7 95.8 35.1 9 2014/03/28 13:00:00 35.4 95.8 38.9 9

Hi R Users, I am going to run a multiple linear regression with around 57 independent variables. Each time I run the model with just 11 variables, the results are reasonable. With increasing the number of independent variables more than 11, the coefficients will get ?NA? in the output. Is there any limitation for the number of independent variables in multiple linear regressions in R? I attached

I installed a 32 bit Windows 2003 enterprise edtion domU. xm list shows the domU has 7G RAM. But Windows 2003 shows only 3.75G RAM. I do not know what''s wrong. Anyone knows? [root@sjd-hot w2k3e]# xm info host : sjd-hot.rashost.com release : 2.6.18.8-xen version : #1 SMP Fri Nov 27 03:53:01 UTC 2009 machine : x86_64 nr_cpus

Dear R list members, I'm encountering a problem with expand.model.frame(): Suppose that I define the following simple function (meant just to illustrate the problem): > fun <- function(model){ + expand.model.frame(model, all.vars(formula(model))) + } > and I have the following model, created with an explicit data argument: > mod Call:

`grDevices::convertColor` performance can be improved by 30-300x with small changes to the code. `colorRamp(space='Lab')` uses `convertColor` so it too benefits from substantial performance gains. `convertColor` vectorizes explicitly over the rows of the input color matrix using `apply`. The level-1 patch [1] illustrates a possible minimal set of changes to achieve this with just R

Hi, I find difficult to read crosstabulated data without percentages, so I wrote this dirty function that may be useful to others. It only works up to 3 dimensions since I am not very good at programming in R. I would appreciate if someone else has a better similar function or can improve this one. As an example of use: > x<-rbinom(100,1,.3) > y<-rbinom(100,1,.3) >

I've seen several posts over the past 2-3 weeks about memory issues. I've tried to carefully follow the suggestions, but remain baffled as to why I can't load data into R. I hope that in revisiting this issue that I don't exasperate the list. The setting: 1 gig RAM , Linux machine 10 Stata files of approximately 14megs each File contents appear at the end of this boorishly long

I've seen several posts over the past 2-3 weeks about memory issues. I've tried to carefully follow the suggestions, but remain baffled as to why I can't load data into R. I hope that in revisiting this issue that I don't exasperate the list. The setting: 1 gig RAM , Linux machine 10 Stata files of approximately 14megs each File contents appear at the end of this boorishly long

Hello, first time posting. I''ve been working with zfs on and off with limited *nix experience for a year or so now, and have read a lot of things by a lot of you I''m sure. Still tons I don''t understand/know I''m sure. We''ve been having awful IO latencies on our 7210 running about 40 VM''s spread over 3 hosts, no SSD''s / Intent Logs.

Thanks for the dput... #### reproducible example of split-apply-combine ### dta <- structure(list(date = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L), .Label = c("2012-01-25 18:00:00",

Hi Jeff, Thank you for the suggestions -- I appreciate your help. Unfortunately, the result2 has two problems... (1) there are now 3 date columns (it looks like 2 cols are merged into 1 col) (2) the output rows should not have any of the basistime dates repeated (maybe I misstated the problem); I need the max fcst value by basistime, but also list the date value for that row; for example:

On Thu, 26 Oct 2017, Thomas Adams wrote: > Hi Jeff, > > Thank you for the suggestions -- I appreciate your help. Unfortunately, the > result2 has two problems... > > (1) there are now 3 date columns (it looks like 2 cols are merged into 1 > col) No, there are two date columns. Result2 includes the grouping value as a row name (pulled from the names of the dta2list items

Hello all! I've been struggling with is for many hours today; I'm close to getting what I want, but not close enough... I have a dataframe consisting of two date-time columns followed by two numeric columns. what I need is the max value (in the first numeric column) based on the 2nd date-time column, which is essentially a factor. But, I want the result to provide both date-time values

Hello, Here is a link to some data: http://www.epa.gov/emap/html/data/surfwatr/data/mastreams/9396/wchem/chmval.txt I am trying to read this in, and want to use: chmval <- read.table("http://www.epa.gov/emap/html/data/surfwatr/data/mastreams/9396/wchem/chmval.txt", sep=",", skip= 84, header=T) the # 84, for 84 lines skipped needs to be derived from the 5th line of the

- Added flush notify functions for NV30 and NV40. - NV30 and NV40 need testing (check for regressions). --- src/gallium/drivers/nouveau/nouveau_stateobj.h | 47 +++++++++++++++++++----- src/gallium/drivers/nv04/nv04_surface_2d.c | 9 +++-- src/gallium/drivers/nv30/nv30_context.c | 3 ++ src/gallium/drivers/nv30/nv30_context.h | 1 +

Hi, I am very new to R and I've been trying to work through the R book to gain a better idea of the code (which is also completely new to me). Initially I imputed my data from a text file and that seemed to work ok, but I'm trying to examine linear relationships between gdist and gair, gdist and gsub, m6dist and m6air, etc. This didn't work and I think it might have something to do

Hi, I need some help with running a recursive function. I like to run funlp2 recursively. When I try to run recursive function in another function named "calclp" I get this "Error: any(!dat2$norm_sd) >= 1 is not TRUE". I have never built a recursive function before so having trouble executing it in this case. I would appreciate any help or guidance to resolve this issue.