similar to: own function: computing time

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

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 all, We have developed our own Affymetrix chip (Custom Express Array, PM-only with two species). I want to analyse the data with the limma package, but for that I need to built my own CDF package, probe package and built the filters to analyse one specie or another. I'm using the makeProbePackage available in the AnnotationDbi (for a R-2.13.0) but I got the following error message:

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

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? ?

Dear all, I have a question concerning the ks.test() function. I tryed to calculate the example given on the German wikipedia page. xi <- c(9.41,9.92,11.55,11.6,11.73,12,12.06,13.3) I get the right results when I calculate: ks.test(xi,pnorm,11,1) Now the question: shouldn't I obtain the same or a very similar result if I commpare the sample and a calculated sample from the distribution?

Thank you very much for your reply. Your code work well with this example. I modified a little to fit my real data, I got an error massage. Error in split.default(x = seq_len(nrow(x)), f = f, drop = drop, ...) : Group length is 0 but data length > 0 On Thu, Jan 31, 2013 at 12:21 PM, arun kirshna [via R] < ml-node+s789695n4657196h87@n4.nabble.com> wrote: > Hi, > Try this: >

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

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,

Dear UseRs, I would like to know which function is the most efficient in finding convex hull of points in 3(or 2)-dimensional case? Functions for finding convex hull is the following: convex.hull (tripack), chull (grDevices), in.chull (sgeostat), convhulln (geometry), convexhull.xy (spatstat), calcConvexHull (PBSmapping). I also would like to know if there is a function that can be used

Dear list, Does anyone have a suggestion (or better still) code for sampling from the uniform distribution over the convex hull of a set of points? Many thanks and best wishes, Ranjan

Dear R-helpers, thanks for yesterday's speeding-up tip. Here is my next query: I have lots of polygons (not necessarily convex ones, and they never have holes) given by x,y coordinates. I want to get the polygon that is the union of these polygons. This is my current method, but I am hoping there is a faster method (up to thousands of polygons, each with ca. 40 xy points). Example:

I am modeling a trend surface using trmat and want to trim the resulting matrix to the area enclosed by my real data (i.e., remove all the extrapolated areas). I was using chull and in.chull to calculate the convex hull and change all the other values created by trmat to NA. However, my real data has portions that are slightly concave so chull would give me slivers that are extrapolations from

Dear List Members, I'm presently carrying out morphological analysis of a data set of neuronal structures. These are essentially 3D binary trees. In due course I will be trying to use discriminant analysis or other methods to classify these neurons based on morphological variables such as total tree length, segment number etc. I would like to calculate a 3D convex hull for a set of X,Y,Z

Dear R gurus and users, I seem to have problem finding the right tool for plotting convex hulls over 2D plots, after a cluster analysis. In fact I would like to draw a convex hull in 2D for a generic group of points. I found a "convhulln", but this doesn't seem to give me a convex hull. Here is what I do: > library(mvtnorm) > Mean <- c(2,1) > Sigma <-

The following seems weird: > format("\pm2") [1] "pm2" > format("\\pm2") [1] "\\\\pm2" > i.e. it seems impossible to set up a x so that "format(x)" returns "\\pm2", and in turn "cat(format(x))" prints "\pm2". ("\pm" is latex for "plus/minus"). R is version 0.64 for win95. I want to

Hi, I seek to identify those points in/outside a multidimensional convex hull (geometry::convhulln). Any suggestions? Background just in case I'm going down a really wrong road: Given an observed data set with one dependent/observed variable (Y) and multiple (3 to 10) independent/design variables (X1, X2, ...) I want to increase the number of points by interpolating. I'm using