similar to: Duda sobre modas en un distribución

Has a test for bimodality been implemented in R? Thanks, John NIWA is the trading name of the National Institute of Water & Atmospheric Research Ltd.

Hi all, I am using Hartigan & Hartigan's [1] "dip test" of unimodality via the diptest package in R. The function dip() returns the value of the test statistic but I am having problems calculating the p-value associated with that value. I'm hoping someone here is familiar with this process and can explain it. In the original article there is an example using n=63 and a

I'm not sure where to begin with this, but I was wondering if someone could refer me to an R package that would test to see if a distribution fits a bimodal distribution better than a unimodal distribution. Thanks, Andrew [[alternative HTML version deleted]]

Dear All, A method for the estimation is univariate unimodal densities (with unknown mode) is described in "Statistical Inference under Order Restrictions" by Barlow et al.. Would anyone know whether there is an R-implementation (preferably with reference) for the estimation of univariate discrete unimodal densities (with unknown mode)? Thanks in advance for your help. Kind

Dear All, Does anybody know if there is a functionality in R to break histograms that show a clear bi-modal (or multi-modal) distribution into a series of unimodal histograms that added up result in the original histogram? I was thinking of using QQ-plots (for which tools are available in R), and then observing the number of times the observed quantiles cross the 1:1 line, but this only gives an

Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: 7bit X-Virus-Scanned: by amavisd-new X-Spam-Checker-Version: SpamAssassin 2.63 (2004-01-11) on hypatia.math.ethz.ch X-Spam-Level: **** X-Spam-Status: No, hits=4.2 required=5.0 tests=MSGID_FROM_MTA_HEADER,RCVD_IN_BL_SPAMCOP_NET autolearn=no version=2.63 Dear r-help list, my question is about ordination technics:

Dear List, I have a set of distributions recorded at an equal interval of time and I would like to plot them as series of horizontal histograms (with the x-axis representing time, and y-axis representing the bins) since the distribution shifts from unimodal to multimodal in several occasions. What I would like to see is something close to a violinplot, but I do not want a kernel density

Hi, I am trying to use the optimize function to optimize a function. The results I am getting don't agree with what I compute on my own and when I look at the graph of f(x) = 100 + ((x-10)**2 + (x-10)) * cos(x-10), where -10 <= x <= 10 in gnuplot. I suspect I am making a mistake in the usage of the R optimize function, perhaps someone could point out where? >

Hi all, I have the data from the posterior distribution for some parameter. I want to find the 95% credible interval. I think "t.test(data)" is only for the confidence interval. I did not fine function for the Bayesian credible interval. Could some one suggest me? Thanks [[alternative HTML version deleted]]

Dear all i could not estimate the optima value or range value in unimodal plot in glm please help me out thanking you regard madan _________________________________________________________________ Hotmail® has a new way to see what's up with your friends. orial_WhatsNew1_052009 [[alternative HTML version deleted]]

Dear all, I new to r and I would like your help. I want to explore the patterns (unimodal, monotonically increased/decreased) of species richness~altitude using GAM in R. Although I run the gam function in mgcv package I do not know how to manually define knots and degrees of freedom. Any help would be greatly appreciated. Spyros -- View this message in context:

Dear Readers: I have two issues in nonparametric statistical analysis that i need help: First, does R have a package that can implement the multimodality test, e.g., the Silverman test, DIP test, MAP test or Runt test. I have seen an earlier thread (sometime in 2003) where someone was trying to write a code for the Silverman test of multimodality. Is there any other tests that can enable me to

Hello I apologise for the length of this entry but please bear with me. In short: I need a way of subsampling communities from all possible communities of n taxa taken 1:n at a time without having to calculate all possible combinations (because this gives me a memory error - using combn() or expand.grid() at least). Does anyone know of a function? Or can you help me edit the combn or

Hi, anyone knows about any functions in R can get multidimensional integration not over a multidimensional rectangle (not adapt). For example, I tried the following function f(x,n)=x^n/n! phi.fun<-function(x,n) { if (n==1) { x }else{ integrate(phi.fun, lower=0, upper=x, n=n-1)$value } } I could get f(4,2)=4^2/2!=8, but failed in f(4,3)=4^3/3! Thanks Best, Lynette

Hi I hope this is the right forum - if not, point me please to a better one. I am using R 2.3.0 on Linux, SuSE 10. I have a question concerning mle (method="BFGS"). I have a few models which I am fitting to existing data points. I realised, that the likelihood is quite sensitive to the start values for one parameter. I am wondering: what is the best approach to identify the right

Hello, I got error message when applying the plot function to the cox.zph object to create the Schoenfeld residual plots. > plot(zph.revasFit[1]) Error in plot.window(xlim, ylim, log, asp, ...) : need finite 'ylim' values In addition: Warning messages: 1: NaNs produced in: sqrt(x$var[i, i] * seval) 2: no non-missing arguments to min; returning Inf in: min(x) 3: no

Suppose i want to compute a 95% highest density for a beta distribution beta(a,b) the two end points x1 and x2 shoudl satisfy the following two equations: pbeta(x1,a,b)-pbeta(x2,a,b)=95% dbeta(x1,a,b)=dbeta(x2,a,b) Is there any fast way to compute x1 and x2 in R? [[alternative HTML version deleted]]

Hi all, I've tried to plot a vector which has two peaks in the density. This link shows the figure. http://docs.google.com/View?docid=dcvdrfrh_1dk9r2rc7 The red line is normal curve and green line is gamma curve. Notice that red line can correctly fit the histogram that has two peaks (i.e. red curve also has two peaks). But the gamma curve there only has one curve. Is there a way I can

I wondered was people on this list felt about this article: http://www.voxeu.org/index.php?q=node/2363 which talks about the problems of obtaining sound answers in numerical optimisation in settings such as MLE or NLS. -- Ajay Shah http://www.mayin.org/ajayshah ajayshah at mayin.org http://ajayshahblog.blogspot.com <*(:-? -

All, Can someone help me create a skewed distribution, mean = 30, with probability of selecting a random number from the distribution greater than or equal 60 equal to 10%? I need the probability density function to equal zero at zero, and have a maximum height at or near 30. Is this possible? And if it is possible, how can I adjust the distribution so that the probability of selecting a