search for: sampe

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

"lpt1" through "lpt9" and "com1" through "com9" are in fact "special" file names under various versions of Microsoft Windows. However, "R Extensions" says only that "lpt1" through "lpt4" and "com1" through "com3" cannot be used as filenames, and "R CMD check" checks for just these

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

(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 <-

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

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

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.

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

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'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

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

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 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

Hi, everyone. I have what I hope will be a simple coding question. It seems this is a common job, but so far I've had trouble finding the answer in searches. I have two matrices (x and y) with a different number of observations in each. I need to draw a random sample without replacement of observations from x, and then, using a matching variable, draw a sample of equal size from y. It is the

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

Hi. The there is an example in nnet help which is pasted in below. I am not sure how they are generating 'targets'. What is the 'class.ind() function doing? In the help docs for it they say "Generates a class indicator function from a given factor." I tried putting a simple vector of the "classes" into test.cl (below) but I get an error of "(list) object