similar to: Beginner question: How to replace part of a filename in read.csv?

Let me start by introducing myself as a biologist with only a little knowledge about programming in matlab and R. In the past I have succesfully created my figures in matlab using the hist3d command, but I have not access to matlab right now and would like to switch to R. I have used the plot command to create a figure of my data and it does almost what I want it to do. My data matrix looks like

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,

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"),

(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

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 <-

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,

Dear all, I am currently analyzing count data from a hierarchical design, and I?ve tried to follow the suggestions for a correct estimation of p-values as discusssed at R-Wiki (http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests&s=lme%20and%20aov). However, I have the problem that my model only consists of parameters with just 1 d.f. (intercepts, slopes), so that the

Dear R users I am trying to obtain p-values for (quasi)poisson lmer models, including Markov-chain Monte Carlo sampling and the command summary. > > My problems is that p values derived from both these methods are totally different. My question is (1) there a bug in my code and > (2) How can I proceed, left with these uncertainties in the estimations of > the p-values? > > Below

G'day all, looking at http://cran.at.r-project.org/web/checks/check_results_Sleuth2.html I noticed that r-prerel-* and r-devel-* issue notes. Apparently, now examples are more thoroughly checked by R CMD check and the note pointed out that a package used in the examples was not declared. This was easily fixed by adding 'Suggests: lattice' to the DESCRIPTION file (now this change has

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

Dear R users I am trying to obtain p-values for (quasi)poisson lmer models, using Markov-chain Monte Carlo sampling and the command summary. > > My problems is that p values derived from both these methods are totally different. My question is (1) there a bug in my code and > (2) How can I proceed, left with these uncertainties in the estimations of > the p-values? > > Below is

I'm creating my own package for personal and I'm having trouble getting it to a point where R (v 2.3.1) will recognise it. I've followed two different tutorials for how to create the package structure and the DESCRIPTION file ( http://web.maths.unsw.edu.au/~wand/webcpdg/rpack.html , http://www.maths.bris.ac.uk/~maman/computerstuff/Rhelp/Rpackages.html#Lin-Lin ). I'm still getting

Hi, Dear all, I am just starting using R in my work and got some trouble to figure out some of the errors. Can anybody help me? The following is the script: read.csv('pupil.txt',header=TRUE,sep='\t')->pupil samp<-c(1:50, 112:162, 171:220, 228:278) pupil.nn2 <- nnet(Type ~ ., data = pupil, subset = samp, size = 2, rang = 0.1, decay = 5e-4, maxit = 200)

R-devel doc/NEWS.Rd (SVN 57472) contains: \item There are two new options for typesetting PDF manuals from Rd files. These are \samp{beramono} and \samp{inconsolata}, and used the named font for mononspaced output. They are intended to be used in combination with \samp{times}, and \samp{times,inconsolata,hyper} is now the default for the reference manual and

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

Duncan Sands <baldrick <at> free.fr> writes: > > > I would be happy if you give me an insight into what could have caused the > > difference. > > No idea. Maybe you forgot to turn optimizations on when compiling? Otherwise > you are going to have to send in your programs along with an explanation of how > you compiled them exactly (exact sequence of

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]]

Hi, Below I have a function mlogl_k, later it's called with "nlm" . __BEGIN__ vsamples<- c(14.7, 18.8, 14, 15.9, 9.7, 12.8) mlogl_k <- function( k_func, x_func, theta_func, samp) { tot_mll <- 0 for (comp in 1:k_func) { curr_mll <- (- sum(dgamma(samp, shape = x_func, scale=theta_func, log = TRUE))) tot_mll <- tot_mll + curr_mll }

Hi all, Is it possible to generate the same sample number of times in R? In SAS, using the option "seed" it is possible to reproduce exactly the same sample. Is there any such feature in R which I can use? For further clarity, for (i in 1:2) { samp = sample(1:1000,100,replace = FALSE) print(samp) } For the above simulation, is it possible to generate the same sampled units

Hello List Inhabitants: I don?t know what this operation is called or if there is a function that does it automatically, hence I seek your help! If I divide a large data collection tasks between two students, and I have a master list of samples, but one student records some of the values, and the other student the remainder, I need to get the two sets of student measurements into one column.