similar to: sapply( ) a loop function

Hi all, I have a dataframe of behavioral observations from 360 fish, each with 241 observation points(rows), which looks like this: > head(d) fish treatment tank trial video tid pid ang.chg abs.ac t len vel d2p x y 1 1 3 1 1 1 1 1 NA NA 0.0 0.000 NA NA 5.169 9.617 2

Hello again R-folks, I'm trying to apply a loop to multiple data frames and then organize the data in a manageable form. I have the code for my loop figured out (thanks to help from this list)...it runs up to 2000 iterations of a "while" loop until it finds a 40-row "d2p" column sum >5 n<-nrow(dsub.f1) test<-0 for(k in 1:2001){ if(k>2000){ break} #stops

Hello Guys, Following up my earlier mail where I am trying to write an alternative front-end for R, I had a question about accessing the closures and environments in R code. Here's the function taken and modified a little from "*Lexical Scope and Statistical Computing*" ===================================================================== f<-function(){

Dear all, I have data like 3 coulmns and many rows. Each entry is less than 10. Example x y z 1 5 3 2 2 3 7 8 3 8 9 5 4 5 4 6 -------------------------- --------------------------- I have to sum entries of each coulmn (seperately) till it be 10. This i have to start for each row. And I want to assign no. of rows needed including that row too(it to be 10 or 10+, the moment it exceeds 10, i

In their paper, "Lexical Scope and Statistical Computing", the authors ( Gentleman and Ihaka ) go to great length explaining why R's use of lexical scoping creates advantages when doing statistical computations. If anyone has or is familiar with this paper, could they provide the main program code for how the "newton" function would be called in their example on page 500

Hi, I have a couple of aggregation operations that I don't know how to accomplish. Let me give an example. I have the following irregular time series time x 10:00:00.021 20 10:00:00.224 20 10:00:01.002 19 10:00:02:948 20 1) For each entry time, I'd like to get sum of x for the next 2 seconds

Hi, I am new in R and have some frustrations as how to set debug breaks during emacs R debug. I use debug () as where or which function to debug. But during the debug, e.g., I have a for loop at the beginning of the function code and want the code execution to jump through that for loop and set a break after that. How to do that? Is there a web site detailing the syntax of the debugging of R?

Hi, I am facing the problem that I want to plot a histogram chart set freq to true and overlay with normal or weibull or exponential distribution curve. The sample code is shown as below: >samp<-c(-8.2262,-8.2262,-8.2262,-8.20209,-8.09294,-8.07321,-8.07321, -8.07321,-8.07175,-8.04948,-8.04948,-8.04948,-8.03848,-8.03848,

I would like to use samp as a part of a filename that I can change. My source files are .csv files with date as the file name, and I would like to be able to type in the date (later perhaps automate this using list.files) and then read the csv and write the pdf automatically. I have tried different combinations with "" and () around samp, but I keep getting the error "object

my reproducible example test<-structure(list(site = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L), .Label = c("A", "B", "C", "D", "E"), class = "factor"),

Hello guys, I would like to ask for help to understand what is going on in "func2". My plan is to generalize "func1", so that are expected same results in "func2" as in "func1". Executing "func1" returns... 0.25 with absolute error < 8.4e-05 But for "func2" I get... Error in dpois(1, 0.1, 23.3065168689948, 0.000429064542600244,

Hello, I would have some details and explanations about the results I get. In fact, I start with a uniform sample between -1 and 1, and then plot its density. My problem is that the density ranges are much more longer than I expected : samp <- runif(10000,-1,1) plot(density(samp)) Instead of varying between -1 and 1, the density varies between approximaly -1.5 and 1.5 Could someone explain

Dear all, suppose I have a bi-variate function f(x,y), I want to find the maxima. I define x and y vector, and get matrix z=f(x,y). how can I get which (x0,y0) makes z become the maxima? I can do two loops to get the x0 and y0, but I think there may exist a function to do this.

My tuneR sawtooth wave function generator is broken. When I use the sine function, I get exactly what I expect: a sine wave whose frequency is defined by the freq parameter. In particular, higher frequencies have shorter wavelengths (more cycles per second means shorter waves). When I create a sawtooth wave, the opposite seems to occur: higher frequencies result in longer waves. But that?s not

(To the list moderator: I just subscribed to the list. Apologies for not having done so longer before trying to post.) Hi all, I am currently using lmer to analyze data from an experiment with a single fixed factor (treatment, 6 levels) and a single random factor (block). I've been trying to follow the online guidance for estimating p-values for parameter estimates on these and other

Hello, everybody, I hope somebody could help me with a dist() function. I have a data frame of size 2*4087 (col*row), where col corresponds to the treatment and rows are species, values are Hellinger distances, I should reconstruct a distance matrix with a dist() function. I know that "euclidean" method should be used. When I type: dist(dframe,"euclidean") it gives me a

I'm new to R (and to S) and am wondering about code from pages 72 and 83 of MASS (Venables+Ripley, 3rd edition), to draw an envelope on a QQ plot. Copying from the book, I've got: #... code whose gist is "a.fit <- nls(..." num.points <- length(resid(a.fit)) qqnorm(residuals(a.fit)) # illustrate data-model residuals qqline(residuals(a.fit)) samp <-

Ccing the maintainer if the tuneR package. Looks to me like sawtooth (and square) don't behave as expected when using xunit="samples". Workaround is to use xunit="time" instead: sawtooth(110,duration=1/100,samp.rate=sample_rate,xunit="time") I looked at the code but found it to be opaque. -- Sent from my phone. Please excuse my brevity. On November 12, 2017

I have a dataframe of animal locations that I need to have in incremental order so that I can calculate the distance traveled between each time step. However, I have identified a few values that don't seem to sort properly. For instance, the last value in the table below should be the first value after sorting, since its time value is '00:01:35'. But, for some reason, it seems to be

Hello there, would you please look into my codes? Here I have following: > set.seed(100) > samp <- sample(c(1,-1,0), 20, replace=T); samp [1] 1 1 -1 1 -1 -1 0 -1 -1 1 -1 0 1 -1 0 0 1 -1 -1 0 Here I want to calculate the length of each unique number for above vector. How can I do that? Thanks in advance [[alternative HTML version deleted]]