search for: animals

Hi, Rsync 3.0.5 on both sides. receiver is Open Solaris and sender is Linux. I got a nested directory - relatively depth but still it should work. It fails instead. sending daemon args: --server --sender -vvlWHogDtpre.is --ignore-errors --numeric-ids --inplace . TEST/ receiving incremental file list delta-transmission disabled for local transfer or --whole-file [...] overflow: xflags=0x7a

Dear all, I'm still learning and transitioning from SPSS to R (1.9.0, winXP) and today I have data from two repeated measures experiments. For each of the subjects I've averaged for two within-SS factors (2 x 2, 4 means per subjects). One experiment had 16 subjects, the other one 25 (between-SS factor exp). So I have something like: avg.cond <- read.table('data.txt') #

...llowing reproduces erroneous results on my system using R-gui: platform i386-pc-mingw32 arch x86 os Win32 system x86, Win32 status major 1 minor 4.1 year 2002 month 01 day 30 language R ##################################################### inter.gp.effect <- 0.1 animals <- data.frame(pos = 0:2) SI.model <- function(Animal.group) { group <- 1 Animal.group$pos[group] <- Animal.group$pos[group] + 1 effective.animals <- Animal.group$pos # allows us to model inter-group contact # effective.animals[1:(length(Animal.group$pos)-1)] <- effe...

For example, c("dog.is.an.animal", "cat.is.an.animal", "rat.is.an.animal"). How can I identify the common prefix is ".is.an.animal" and delete it to give c("dog", "cat", "rat") ? Thanks _________________________________________________________________ [[alternative HTML version deleted]]

Hi all, I have a population in which I want to follow living and dead animals through time ( 1 simulation, 100 years). I have created 2 arrays for living and dead animals In the starting population there are, say, 500, animals To determine whether each of these animals survives to a following age-class, a uniformal chance is generated, resulting in "TRUE" if the a...

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...re is super easy solution, just not sure what it is. Please see short example below. ?I would like to get the frequency (counts) of all the variables in a single column (that is easy), but I would also like to return the value 0 for the absence of variables defined in another column. For example: animals = matrix(c('cat','tiger','cat','tiger','fish','fish','dog','dog'),ncol=2, byrow=F) animals = as.data.frame(animals) table(animals$V1) # Returns the count for the variables in the first column as cat tiger ? ?2 ? ? 2 # But I would l...

...iable from the first SELECT to an integer variable... Any suggestions? Thanks - Bodil I use the following code: raw<-sqlQuery(.zz, 'SELECT TOP(100)PERCENT Animal.Herdnumber AS herd, Animal.ChrNumber AS chrNr, Animal.AnimalNumber AS animalid, Animal.DateOfBirth AS datebirth, AnimalStatus.Code AS codestatus, AnimalStatus.Description AS animalstatus, AnimalTransfer.Date AS date, AnimalTransferType.Code AS codeevent, AnimalTransferType.Description AS event FROM Animal FULL JOIN AnimalTransfer ON Animal.AnimalNumber = AnimalTransfer.AnimalNumber FULL JOIN...

...aken from the finite set given by levels. It is important that this object is not numeric; in particular, comparisons and other operations behave AS IF THEY OPERATED ON VALUES FROM THE LEVELS SET, WHICH IS ALWAYS OF MODE CHARACTER. Let's try comparisions on values from the level set: > my.animals <- c(4,5,6,4,5,6) > my.levels <- 4:6 > my.labels <- c("dog","cat","rat") > animals <- factor(my.animals,levels=my.levels,labels=my.labels) > unclass(animals) [1] 1 2 3 1 2 3 attr(, "levels"): [1] "dog" "cat" "r...

Hi, I tried on this, but couldn't figure it out: Suppose I have a dataframe as follows: dat <- data.frame(Day=rep(rep(c(1,2), each=4),2), Animal = rep(c(1,2), each=8), Count=c(rnorm(8, 100), rnorm(8,90))) 2 animals are being examined on 2 different days. Count is the result. Now I need to point out whether or not there is a difference between the days. I did this by an ANOVA test, while first converting the animal and day to a factor variable: dat$Animal <- as.factor(dat$Animal) dat$Day <- as.factor(da...

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, The minimize plugin conflicts with Animation. For example, it doesn't let Animation draw shade animations, and interferes with other window event animations. The animation plugin now minimizes the relevant effects to taskbar, so using the two plugins together doesn't make sense anymore. Moreover, by default Animation is off, Minimize is on, and when users enable Animation, naturally

Hi, I have an experiment with 2 independant factors which I have been trying to analyse in R. The problem is that there are several data points recorded on the same animal. However, no combination of treatments is repeated on the same animal. All possible combinations of treatments are done in a random order with as many points as possible being done on 1 animal before moving onto the next. The

Hi, Having the minimize_open_close option in Fade wasn't enough for conflict resolution with Animation, since it was on by default. This makes sense since the Minimize plugin is used by default, which is a lightweight animation provider that some people/distributions might prefer over Animation. And nobody really needs to know that this option resolves the conflict. So here is a better method

1. Emma is performing an experiment that requires individual handling of some animals. The sizes of the animals are lognormally distributed: The natural logarithms of their sizes has a normal distribution with mean 3 and standard deviation 0.4. The time (in minutes) it takes to handle each animal is given by 10 + s · 1.5 + eε for animals with s ≤ 20 20 + s · 0.8 + eε for animals wi...

I want to use select form elements to choose between boolean options. How can I have it default to true and still display the persisted value (either true or false) when editing an existing object? I guess booleans default to false by default so its not obvious how to recognize when it''s a real ''false'' that the user set or default false because the value was null.

Dear helpers, I'm trying to replace a character with a unicode code inside a data frame using gsub(), but unsuccessfully. > data.frame(animals=c("dog","wolf","cat"))->my.data > gsub("o","\u0254",my.data$animals)->my.data$animals > my.data$animals [1] "d??g" "w??lf" "cat" It's not that a data frame cannot have unicode codes, cf. e.g. > dat...

Hi everyone, I am doing an analysis of reviews in IMDB and am running into trouble getting my data into the right shape for analysis. Key question: I want to know for each word in the IMDB, whether it is over- or under-represented in a particular category (Rating x Genre). I was figuring on estimating this with a g-test, fwiw. But the basic question I'm asking here is about data

Dear R users, Suppose I have an vector like this: animal <- c("Tiger","Panda") I would like to know is there any function that check for the existence of certain item in a vector. e.g. > func("Tiger",animal) # check for the existence of "Tiger" TRUE > func("Acacia",animal) #Acacia is not an item of the animal vector FALSE I know

...unch of stuff, and want to generate variables with my output. (I could make a "list of lists" and name all the elements, but I really want separate variables.) ################# #This is just a dummy example, please excuse any shortcuts... data <- read.table("file", ....) animals <- (data[,animal]) animals > "cat", "dog", "horse" # Not known what these are before I read the data file # do a bunch of stuff mean_cat <- abc var_cat <- dfd mean_dog <- 123 var_dog <- 453 etc.. ############## I thought of trying to use the pas...