search for: bimodal

We currently ship a PAE 32-bit domU that we can trivially make bimodal, except that if we set it to "bimodal", then older Xens will default to thinking the domU is not PAE: 353 dsi->pae_kernel = PAEKERN_no; 354 if ( dsi->__elfnote_section ) 355 { 356 p = xen_elfnote_string(dsi, XEN_ELFNOTE_PAE_MODE); 357 if ( p != NULL &amp...

Hello everyone, I'm trying to use mle from package stats4 to fit a bi/multi-modal distribution to some data, but I have some problems with it. Here's what I'm doing (for a bimodal distribution): # Build some fake binormally distributed data, the procedure fails also with real data, so the problem isn't here data = c(rnorm(1000, 3, 0.5), rnorm(500, 5, 0.3)) # Just to check it's bimodal plot(density(data)) f = function(m, s, m2, s2, w) { -log( sum(w*dnorm(data, mean=m...

Dear R users, I'm looking for a test of bimodality in order to make some decisions about how to procede with an analysis algorithm. I have not come across any such tests in my readings and discussions apart from the Rao which appears to be applicable to cyclic data. The data I'm interested in characterizing as uni- or bimodal are frequency...

Hi, I was looking for a package that would help with outlier detection for bimodal distributions. I have tried 'outliers' and 'extremevalues' packages, but am not sure if they are ok for bimodal distribution. Any help would be highly appreciated! thanks, [[alternative HTML version deleted]]

Hi, Does anybody have a good tip of how to treat bimodal data to perform statistical analyses? My data set ranges from -1 to 1 (any values are posssible in between) and most data are either close to -1 or close to 1. They are the results of a two choice experiment where individuals could choose more than once in either direction and scores were calculate...

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.

Hello, Is there any test  for bimodality in R that x <- c(rnorm(1000,0,1),rnorm(1000,3,1)) hist(x,nclass=100) Thank you in advance for any help. Regards, Samor [[alternative HTML version deleted]]

...1.5 25.3 [157] 65.2 39.5 And the following parameter set (2 component) for gamma function. comp.1 comp.2 alpha (shape) 2.855444 2.152056 beta (scale) 10.418785 39.296224 These params are predefined/precalculated by user. My question is how can I create a bimodal gamma curve - based on the two parameter set - on top of the histogram of data points above? - Gundala Viswanath Jakarta - Indonesia

Hi, is there any package/function that can tell if a numeric vector (continuous data) has a bimodal or trimodal distribution and caluclate the location of the corresponding modes? Thanks

...he improvedLHS function and have used it to generate a bunch of properly distributed uniform probabilities. Now I am using functions like qlnorm to transform that into the appropriately lognormal or triangularly distributed parameters for my modes. However I have a parameter which I believe is bimodally distributed, could someone please point me at an appropriate function equivalent to qlnorm which I can use, because for some reason I have been unable to find one. It occurs to me that maybe one doesn't exist, in which case could someone give me some other idea of how to accomplish this g...

Hi All, I have a parameter that is bimodal, and I want to get some sort of linear model done with it results = some.linear.function(bimodal.param ~ factor1 + some other stuff, mydata) I want to see if factor 1 matters (it has 3 levels, of of which can be taken as baseline), i.e: summary(results) Coefficients: Estimate Std. E...

Hi Everyone- After searching through posts and my favorite R-help websites I'm still confused about a problem. I have data which is bimodal in nature, but there is no clearly obvious separation between the two peaks. In programs such as Origin, I can deconvolute the two distributions and have it generate a "best guess" as to what the two subpopulations are which make up my dataset. Below is a link to a figure which represen...

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]]

For several years, I have been using Splus to analyze an ongoing series of datasets that have a bimodal distribution. I have used the following functions, in particular the ms() function, to estimate the parameters: two means, two standard deviations, and one proportion. Here is the code I've been using in S: btmp.bi <- function(vec, p, m1, m2, sd1, sd2) { (exp(p)/(1+exp(p)))*...

...ción (el resto esta en el fichero adjunto con las distribuciones kernels y las soluciones gráficas). *Distribución #1(suponía que hay más de una moda)* Hartigans' dip test for unimodality data: Datos8$V2 D = 0.0432, p-value = 0.3501 alternative hypothesis: non-unimodal, i.e., at least bimodal *Distribución #2* dip.test(Datos9$V2) Hartigans' dip test for unimodality data: Datos9$V2 D = 0.0667, p-value = 1.535e-06 alternative hypothesis: non-unimodal, i.e., at least bimodal Podría alguien por favor darme alguna pista. Gracias Justo ------------ próxima parte -------...

Hello R users, I am trying to estimate the parameters of a bimodal normal distribution using moments matching, so I have to solve a non-linear system of equations. How can I solve the following simple example? x^2 - y^2 = 6 x ? y = 3 I heard about nlsystemfit, but I don?t know how to run it exactly. I have tried the following code, but it doesn?t really work:...

Hello, What I am trying to do is: Generate a density plot of a population of data. This data has a bimodal distribution so I've isolated a couple of possible sub-populations and I want to overlay these two density plots over the first to see whether they are contributing to the bimodal population. I can do this fine with plot(density(...)) and lines(density(...)) . But the resulting plots seem to...

...e horizontal violin plots. I have tried both vioplot and simple.violinplot, but both of them seem to not be willing to take the horizontal option. Is this correct, or am I just bungling it somehow? For instance, for vioplot (from the example shown, with the horizontal modification): > vioplot(bimodal,uniform,normal, horizontal=TRUE) Error in median(data) : need numeric data > Karin -- Karin Lagesen, PhD student karin.lagesen at medisin.uio.no http://www.cmbn.no/rognes/

Dear R helpers, I have a bimodal dataset dealing with loss amounts. I have divided this dataset into two with the bounds for the first dataset i.e. dataset-A being 5,000$ to 100,000$ and the dataset-B deals with the losses exceeding 100,000$ i.e. dataset-B is left truncated. I need to fit truncated normal disribution to dataset...

I am creating a CDF plot function more user-friendly than any default r function. Depending upon the bimodality of the data (it is often bimodal), or any other strange data trends, the points can end up gathering in just about any corner of the plot. So, when I add a legend, whether I choose to add it in the bottom right, top left, or wherever, it will sometimes end up putting the legend right on the dat...