similar to: ks.test() with 2 samples vs. 1 sample an distr. function

In the first example you are performing a one-sample test against a continuous cumulative distribution (in this case a normal distribution). In the second case you are performing a two-sample test. You drew your values for x non-randomly by specifying fixed intervals along a normal distribution, but ks.test() just sees that you have provided two samples, not one sample and values along a

I have a file: x y z 0.025 0.025 1.65775 0.025 0.050 1.62602 0.025 0.075 1.63683 0.025 0.100 1.91847 0.025 0.125 2.00913 0.025 0.150 1.82222 0.025 0.175 1.70901 0.025 0.200 1.39759 0.025 0.225 1.39089 0.025 0.250 1.04762 If I read the file like this: data<-read.table("file.dat") How do I access the vectors x,y,z that are inside the dataframe data? I studied Venables and

Dear R users, I'm trying to do betareg on my dataset. Dependent variable is not normally distributed and is proportion (of condom use (0,1)). But I'm having problems: gyl<-betareg(cond ~ alcoh + drug, data=results) Error in optim(par = start, fn = loglikfun, gr = gradfun, method = method, : initial value in 'vmmin' is not finite Why is R returning me error in optim()? What

Dear List, I have a data frame with approximately 500000 rows that looks like this: ?Date??? time??? value ? 19.07.1956????????? 12:00:00?????????????? 4.84 19.07.1956????????? 13:00:00?????????????? 4.85 19.07.1956????????? 14:00:00?????????????? 4.89 19.07.1956????????? 15:00:00?????????????? 4.94 19.07.1956????????? 16:00:00?????????????? 4.99 19.07.1956????????? 17:00:00?????????????? 5.01

Dear helpers I constructed a data frame with this structure > str(dados1) `data.frame': 485 obs. of 16 variables: $ Emissor : int 1 1 1 1 1 1 1 1 1 1 ... $ Marisca.Rio : int 1 1 1 1 1 1 1 1 1 1 ... $ Per?odo : int 1 1 1 1 1 1 1 1 1 1 ... $ Reproducao : int 3 3 3 3 3 3 3 3 3 3 ... $ Estacao : int 2 2 2 2 2 2 2 2 2 2 ... $ X30cm : int

Hi all, I wrote a function that actually does what I want it to do, but it tends to be very slow for large amount of data. On my computer it takes 5.37 seconds for 16000 data points and 21.95 seconds for 32000 data points. As my real data consists of 18000000 data points it would take ages to use the function as it is now. Could someone help me to speed up the calculation? Thank you, Tonja

Dear List I hope you can help me: I?ve got a dataframe (df) within which I am looking for Peak Over Threshold values as well as the length of the events. An event starts when walevel equals 5.8 and it should end when walevel equals the lower threshold value (5.35). I tried ?clusters (?)? from ?evd package?, and varied r (see example) but it did not work for all events (again

Hi all, I used contour() to add contour lines to a plot. Now I?m wondering if there is a way to get an output of the calculated x- and y- coordinates of the contour lines? Tonja

Hi all! I'm sure this is a stupid question but I can't find an answer. How can I fit the Gumbel distribution to my data using The Method of Moments in R? Thank you for helping me, Tonja

Hi all, I have a package that is specific to a task I was repetitively using a few years ago. I now needed to run it again with new data. However I am told it was built with an older version or R and will not work. How can I tweak the package so it will run on 11.1? It was a one-off product and has not been maintained. Is there a way to "unpackage" it and repackage it to work? I

Dear all,I am a new user of WinBUGS and need your help. After running the following code, I got parameters of beta0 through beta4 (stats, density), but I don't know how to get the prediction of the last value of h, the variable I set to NA and want to model it using the following code.Does anyone can given me a hint? Any advice would be greatly appreciated.Best

Dear R-helpers ? I have 7 data points that I want to fit a continuous curve to, that should look similar to a sine wave My data points would mark the local minima and maxima respectively. This is what I?ve got so far. And I would keep doing so, but sadly nls() then says that it has reached the maximum number of Iterations? ?

Hello. I asked before and it was great, cause as a beginner I learned a lot. But, if I have this in R (1 and 2 are codes for sex): > sex<-c(1,2,2,1,1,2,2,2) > sex [1] 1 2 2 1 1 2 2 2 I´d like to obtain the proportion according to sex.So I type: > prop.table(sex) [1] 0.07692308 0.15384615 0.15384615 0.07692308 0.07692308 0.15384615 0.15384615 [8] 0.15384615 The result is OK, but I

Hello all, Can someone tell me why the following mixture of two log-normal distributions does not get truncated? What puzzles me is that the function works almost always, but for certain combinations (like the one below), it does not. # R code example library(distr) mix<-UnivarMixingDistribution(Lnorm(3.2,0.5),Lnorm(5.4,0.6),mixCoeff=c(0.3,0.7))

We would like to announce the availability on CRAN of a new version (1.5) of our package "distr" . ----------------------------------------------------------------------------------------- Changes from 1.4 to 1.5 -package is now using /lazy loading/ -minor changes in the help pages -minor enhancements in plot for distributions (Gamma, discrete distributions) -package now includes a

We would like to announce the availability on CRAN of a new version (1.5) of our package "distr" . ----------------------------------------------------------------------------------------- Changes from 1.4 to 1.5 -package is now using /lazy loading/ -minor changes in the help pages -minor enhancements in plot for distributions (Gamma, discrete distributions) -package now includes a

Hi List! I?m using regsimq() from the ?lmomRFA?-package to calculate error bounds for diverse distributions. For example: regsimq(gumfit$qfunc, nrec = lmom.data$n, f = lcdfgum, boundprob = c(0.025, 0.975)) Several times I got this error massage: Fehler in quantile.default(ou, probs = boundprob, type = 6) : missing values and NaN's not allowed if 'na.rm' is FALSE So my question

Dear List I?m using the ?lmomRFA? package to fit different distributions to my data sample. To calculate the error bounds I used: regsimq(?) and sitequantbounds(?) So my questions are: Are error bounds and confidence intervals the same thing? And: Does regsimq(? boundprob = c(0.05, 0.95)) calculate the 90 or the 95% confidence interval? If error bounds and confidence intervals are

Hi List, Can someone help me to calculate the coordinates of the red and green points? In this example I found their approximate location by trying, but as I have to analyse many similar curves, I?d rather calculate the exact location. data<- c(0.008248005, 0.061242387, 0.099095516, 0.189943027, 0.227796157, 0.258078661, 0.280790538, 0.303502416, 0.386779301, 0.454914934, 0.545762445,

We would like to announce the availability on CRAN of a new version (1.4) of our package "distr" . ----------------------------------------------------------------------------------------- Changes from 1.3 to 1.4 -To avoid name collisions with short forms for TRUE and FALSE: classes T and F (T- and F-distributions) renamed to Td and Fd -The package is now loaded as a binary =>