search for: multimodes

Dear all Please, is there any function or package for dealing with multimodal distributions? I try to fit multimodal distribution or more precisely to find out mixture of normal distributions which can lead to my actual data. I use optim to find (in that case) two parameters but what I want is to let the function find out arbitrary number of normal distributions underlaying my actual data

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

Dear R mailing list members, ? I am trying to find a way to assign samples into groups depending on their mathematical distribution in a computational way (that is, looped many times). My input is by row, a series of 34 samples per row with n rows. The goal would be to compute the distribution of row n and assign for that row n the samples into bins that would match the distribution of the given

Hello, I downloaded R today because I was told it has very good bootstrapping abilities. What I need to do is to program it (or use an existing program) to bootstrapping test for multimodality using nonparametric kernel density estimates as proposed by Efron and Tibshirani (1993). If anyone can get me started, I will be immensely grateful. Thanks. Sangeeta

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

Dear R-users, I would like to know if there is a function (in base R or the extension packages) that would automatically detect the break points in a vector x for later use in the cut function. The idea is to determine the boundaries of the n intervals (n>=1) delimiting clusters of data points which could be considered "reasonably" close, given a numerical vector x with unknown

Dear R users, I am interested in uni- bi- multimodality tests, for analysing reaction times data. I was lead to Hartigan's dip test (Ann. Statistics, 13, 1985, pp. 70-84, Applied Statistics, 34, 1985, 320-325). Not being a programmer I am unable to translate the Fortran code given in ref. 2 into a R function. I'd be glad to learn that someone already did it, or has devised a better

Dear all. RE how to estimate parameters of multimodal distribution Thank to prof.Ripley for pointing me to mclust package, although I am not sure I can apply it to my problem. I have another question. I need to change some of my values in data frame to NA. I use something like df[df$v1 < 5, 5:10] <- NA which is OK if there are no NA values in v1. here are some foo attempts >

Hi, I don't mean to be annoying, but it seems like there isn't any interest in partial authentication. Is this true? It's not a future plan for OpenSSH to have this feature? I'd just like to know if I'm on my own or not. Thanks Erik.

I frequently want to test for differences between animal size frequency distributions. The obvious test (I think) to use is the Kolmogorov-Smirnov two sample test (provided in R as the function ks.test in package ctest). The KS test is for continuous variables and this obviously includes length, weight etc. However, limitations in measuring (e.g length to the nearest cm/mm, weight to the nearest

Dear R users, I've written the following functions to implement Silverman's modality test ("Using kernel density estimates to investigate multimodality", J.R. Stat. Soc. B, 43, (1981), 97-99.), and I tested them on the Chondrite data set (Good & Gaskins, J. Amer. Stat. Ass., 75, (1980), 42-56). Values for the critical window width seem OK, which is not the case for the

Hi I have a large dataset which follows a multimodal distribution. And I would like to identify the maxima. As the data is obtained from a stochastic simulation, not all maxima in the data are "real maxima of the dirstribution" but rather small random fluctuations. Unfortunately, it is not possible for me to run more simulations to smooth the obtained distribution. What I am doing

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

My problem is I have data with both categorial and numerical data, currently only the categorical number contains missing data, was wondering do I make a new dataframe containing only the categorical columns? How would you use Latent Class Model specifically poLCA to impute the missing data? http://www.sscnet.ucla.edu/polisci/faculty/lewis/pdf/poLCA-JSS-final.pdf The reason why I chose not to

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]]

> > It would be nice not only for me. > > I agree totally. If you belong to R-contributors group then thanks a lot in advance! > The problem is that you have to formalize what a cluster is, > and this is not a well defined notion. > It has different meanings in different applications. you are right if one follows the idea of full formalization of the notion it

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

I'm having a problem with automount (autofs) from a server running CentOS 5.4 to clients (example is CentOS 5.4). Client pulls automount maps from NIS. THIS particular server is also used for login so it is NIS bound as well (other servers are NOT). ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ NIS Server Side... (content shortened)

I have a problem receving calls via the ISDN line, using the followin components Asterisk 1.0.9 with asterisk@home chan_capi-cm-0.6 AVM Fritz card datalink protocol = point to multimode I can make calls out with no problems so the issue is only incoming calls. When I make the call from an external line to the ISDN line connected to asterisk, I get a busy signal after about 5 seconds. I have

>Or, you could use a Corinex Phone Line Bridge which runs 128Mbits up to 2000 >feet. They also have a co-ax version which is 200mbits and goes 4000 feet... >About $300 for both ends. too bad they don't say what the bandwidth is at max distance - anyone know?