similar to: How to make matrix missing data 0

Dear R Users, I was using R to import five years traffic data, but the error always come up as shown below. The data frame contains 12 columns and unknown number of records. Would you have any ideas that how I should deal with this situation?? Many thanks for any hints. >wim<-sqlQuery(channel,qry) Error: cannot allocate vector of size 24.0 Mb In addition: There were 16 warnings (use

Full_Name: Ed Borasky Version: 1.8.1 OS: Windows XP Professional Submission from: (NULL) (208.252.96.195) R 1.8.1 seems to be running into a memory allocation problem in the "aggregate" function. I have a rather large dataset (14 columns by 223,000 rows -- almost 40 megabytes) and a script that performs some processing on it. The system is a 768 MB Pentium 4. Here's the console

Hi all, I am trying to interparete the result of the following output from lm; fit1 =lm(Feed _Intake ~ weight + season + weight*season) Season has three classes(x,y,z) Reults are Estimate (Intercept) 21.51559 weight 2.13051 factor(season)y 10.59739 factor(season)z 1.30421 weight:factor(season)y

Does anybody knows how to make the game run? It installs just fine, but won't run. I have been searching all over the web to find a solution, but not haven't found a single webpage or thread about it?

On Thu, May 03, 2018 at 01:09:30AM -0400, Kevin Korb via rsync wrote: > --delete only works when you sync a dir not individual files. So... > rsync -vai --delete --include='g*' --include='G*' --exclude='*' > /share/Public/videos/ /share/Backup-HDD-03 That kinda didn't work: rsync -vai --delete --include='S[A-Z]*' --include='S[a-h]*'

Hi, I am trying to assign "Season" values to dates depending on when they occur. For example, the following dates would be assigned the following "Season" numbers based on the "season" intervals detailed below in the code: ddate Season 29/12/1998 20:00:33 1 02/01/1999 05:20:44 2 02/01/1999 06:18:36 2 02/02/1999

rsync version 3.1.2 protocol version 31 I've run into an issue using rsync on my QNAP NAS. I've installed Entware-ng on the NAS so that I can install better versions of programs, rsync being one of them. But, I've run into an issue wqith using the --delete option, as it has problems using wildcards. Initially a backup script looked like: #!/bin/sh for d in

Hi all I can't find what I am looking for so I am asking here. I have a dataset that looks something like this. Year season percent_below 2000 Winter 6.9179870 2000 Spring 1.6829436 2000 Summer 1.8463501 2000 Autumn 3.8184993 2001 Winter 2.8832806 2001 Spring 2.5870511 2001 Summer 0.0000000 2001 Autumn 4.7248240 2002 Winter

Dear all, Apologies for this beginner's question. I have a variable Price, which is associated with factors Season and Crop, each of which have several levels. The Price variable contains missing values (NA), which I want to substitute by the mean of the remaining (non-NA) Price values of the same Season-Crop combination of levels. Price Crop Season 10 Rice Summer 12

Hello all, I cannot seem to figure out this seemingly simple procedure. I want to sort a data frame by a specified character vector. So for : df.. <- data.frame(Season=rep(c("Summer","Fall","Winter","Spring"),4),Obs= runif(length(rep(c("Summer","Fall","Winter","Spring"),4)))) I want to sort the data frame

I've got a problem with the sparseby command (reshape library), and I have reached the peak of my R knowledge (it isn't really that high). I have a small data frame of 23 rows and 15 columns, here is a subset, the first four columns are factors and the rest are numeric (only one, line54 is provided). bearID YEAR Season SEX line54 5 1900 8 3 0 16.3923519 11 2270

Dear all, How can I run a constrained correspondence analysis with the following data: 15 animals were measured repeatedly month-wise (over to 2 years) according to ther diet composition (8 food categories). our data.frame looks like this: food 1 2 ... 8 sex season year animal freq 12 8 ... 1 0 summer 2011 1 freq 0 7 ... 0 1 winter 2011 1 ... freq 0 7 ... 0 1 spring 2011 15 We

Hi, I was wondering if someone could please help me. I am doing a logistic regression to compare size at maturity between 3 seasons. My model is: fit <- glm(Mature ~ Season * Size - 1, family = binomial, data=dat) where Mature is a binary response, 0 for immature, 1 for mature. There are 3 Seasons. The Season * Size interaction is significant. I would like to compare the size at 50%

Hi, I was hoping to get some advice regarding the testing of interactions, when one factor is modelled as a random effect... I have a model with binomial error structure where the response variable is the proportion of time spent at the main sett (animals were tracked for 28 consecutive days in each season, and were recorded either at the main sett or an outlier sett, so the response variable is

Does anyone know of a way of dealing with unbalanced mixed effects (fixed and random factors) for fully factorial designs. An example of such data is given below; The response variable is SQRTRECRUITS SEASON is a random factor DENSITY is a fixed factor Thus DENSITY:SEASON is a fixed factor. Therefore, whereas the effects of SEASON and DENSITY:SEASON should be tested against the overall

Hi all, I have a couple of questions. 1) Is there a more effective way to remove the following pattern (patternrm) from the station_id_Timeseries (see below) patternrm <- c(_2000_4_OND, _2001_1_JFM, _2001_2_AMJ, _2001_3_JAS, _2001_4_OND, _2002_1_JFM, _2002_2_AMJ, _2002_3_JAS, _2002_4_OND, _2003_1_JFM, _2003_2_AMJ, _2003_3_JAS, _2003_4_OND, _2004_1_JFM, _2004_2_AMJ, _2004_3_JAS, _2000_4_OND) #

Hi list, I was searching how to properly write a command line for a mixed ANOVA. Well honestly, there are so many material on the older post of the list that just confused me. I have five factors. Season (fixed) Beach (fixed) Line (fixed) Block (random) Strata (random) nested in Block And for each of the tree strata per block I got 3 replicates. I saw lots of things about

Hi, I am a consultant in Quality Management. I am exploring the use of R with any GUI - R commander/Rkward for doing analytical work. Have installed R, R Commander and Rkward. I hope to learn by doing various exercises that I use for teaching analytical techniques to my clients. I would be posting the data on this mailing list, and the rkward mailing list wherever I get stuck. First such

Hello everybody, I need to calculate seasonal means with temperature data for my work. I have 70 files coming from weather stations, which looks like this for example: startdate <- as.POSIXct("01/01/2006", format = "%d/%m/%Y") enddate <- as.POSIXct("05/01/2006", format = "%d/%m/%Y") date <- seq(from = startdate, to = enddate, by =

hello, I have been trying to use the predict function in the vars package to forecast from a seasonal VAR model. The following code sample illustrates what I am trying to do and the error that I get when trying to do it. I run the following code, that results in the following error: data(Canada) endoC <- Canada[1:72,1:3] exoC <- Canada[1:72,4] var.2c <- VAR(endoC, p = 2,