similar to: density function

Hi, I used the density function in the R package, and got the following results. I just wonder how to explain them. What is Min, 1st Qu, Median, and so on? I could not find an explanation from help(density). The plot doesn't seem to match the x and y value either. Thanks in advance for any help that you can give me! Hui ------------------------------------------------------------ Call:

Hi, I was using a density estimation function as follows: > est <- KernSmooth::bkde(x3, bandwidth=10) When setting bandwidth less than 5, I got the error "longer object length, is not a multiple of shorter object length in: kappa * gcounts ". I wonder if there is anybody who can explain the error for me? Thanks! Hui

Dear Knowledgeable R Community Members, Please excuse my ignorance, I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance. I have a finite mixture modeling problem -- for example, a 2-component gaussian mixture -- where the components have a large overlap, and I am trying to use the "mclust" package to solve this problem. I need

Hi people, Does anybody know some Density-Based Method for clustering implemented in R? Thanks, Fernando Prass _______________________________________________________

Dear R-Users I would like to estimate a constrained bivariate normal density, the constraint being that the means are of equal magnitude but of opposite signs. So I need to estimate four parameters: mu (meanvector (mu,-mu)) sigma_1 and sigma_2 (two sd deviations) rho (correlation coefficient) I have looked at several packages, including Gaussian mixture models in Mclust, but I am not sure

Hi all, I have a question regarding the density function which gives the kernel density estimator. I want to decide the bandwidth when using gaussian kernel, given a set of observations. I am not familiar with different methods for bandwidth determination. Below are the different ways in R on deciding the bandwidth. Can anyone give an idea on which ones are preferred. Also, how can I take

Dear Knowledgeable R Community Members, Please excuse my ignorance, I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance. I have a finite mixture modeling problem -- for example, a 2-component Weibull mixture -- where the components have a large overlap, and I am trying to adapt the "mclust" package which concern to normal

I am using the following commands for plotting kernel density for three kinds of crops density(s22$Net_income_Total.1, bw="nrd0",adjust=1, kernel=c("gaussian"))->t plot(t, xlim=c(-30000,40000), main="Net Income Distribution", axes=F, ylim=c(0,0.00035). xlab="Value in Rupees") par(new=T) density(s33$Net_income_Total.1, bw="nrd0",adjust=1,

Dear R help group: I am attempting to produce a density plot from a list of 20000 values using the density.lf function and would appreciate any help, I hope I have done my homework reading the documentation but I still seem to be missing something basic. I have read the data as a table using read.table, with header=TRUE (I excluded 2000 values), when calling the objects it appears to be there and

Please keep the list in cc. Sorry, it didn't work as expected. Maybe someone else have an appropriate solution. Best, Ulrik On Sa., 26. Aug. 2017, 12:57 niharika singhal <niharikasinghal1990 at gmail.com> wrote: > Hi > > Thanks for you mail, > I really appreciate your time on my problem > > I have posted this problem on > > >

> No HTML this time. Sorry Dear all, I am attempting to model some one-dimensional data using Gaussian mixture model with mclust.? Generally, the data that I have have 3 overlapping populations (with one of them being the majority, and the other two combining to less than 15%) and for some reason, mclust consistently ignores the smaller peaks, giving me strange values for the means

Dear R-list, I have made a simple kernel density estimation by x <- c(2,1,3,2,3,0,4,5,10,11,12,11,10) kde <- density(x,n=100) Now I would like to know the estimated probability that a new observation falls into the interval 0<x<3. How can I integrate over the corresponding interval? In several R-packages for kernel density estimation I did not found a corresponding function. I

Hello! Someone know what are the difference between R and S-PLUS in the density() function? For example, I would like to reply this simple S-PLUS code in R, but I don't understand which parameter I should modify to get the same results. S-PLUS CODE: density(1:1000, width = 4) R-CODE: density(1:1000, bw = 4, window = "g", n = 50, cut = 0.75) I obtain the same x values, but

Hey, Dose R include some package for Gaussian Mixture Model data generation and parameters estimation? Now I want to assign lots of multivariate data into a GMM model. So just wondering if given sample data, can we use some functions to estimate the compoents' density function. Thanks for your support. Fred -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

Hello I am trying to find an automated way of fitting a mixture of normal and log-normal distributions to data which is clearly bimodal. Here's a simulated example: x.1<-rnorm(6000, 2.4, 0.6)x.2<-rlnorm(10000, 1.3,0.1)X<-c(x.1, x.2) hist(X,100,freq=FALSE, ylim=c(0,1.5))lines(density(x.1), lty=2, lwd=2)lines(density(x.2), lty=2, lwd=2)lines(density(X), lty=4) Currently i am using

Is there code for bivariate kernel density estimation? For bivariate kernels there is kde2d in MASS kde2d.g in GRASS KernSur in GenKern (list probably incomplete) but none of them seems to accept a weight parameter (like density does since R 2.2.0) -- Erich Neuwirth, University of Vienna Faculty of Computer Science Computer Supported Didactics Working Group Visit our SunSITE at

Hi all, I'm working with radar remote sensing data and want to measure the height of 3d spikes created by backscatter from bright objects. My thought is to fit a gaussian density function to each spike and extract the x, y and z location of the peak. Can anybody give me a hint of how to do this? Thanks, Alan [[alternative HTML version deleted]]

> My understanding is that this represents bivariate normal > approximation of the data which uses the kernel density function to > test for inclusion within a level set. (please correct me) You can fit a bivariate normal distribution by computing five parameters. Two means, two standard deviations (or two variances) and one correlation (or covariance) coefficient. The bivariate normal

Hello, I am trying to find out if R can do the following: I have a mixture of normals say f = 0.2*Normal(2, 5) + 0.8*Normal(3,2) How do I find the difference in the densities at any particular point of f and at Normal(2,5)? -- Thanks, Jim. [[alternative HTML version deleted]]

Dear R users, This is a KDE beginner's question. I have this distribution: > length(cap) [1] 200 > summary(cap) Min. 1st Qu. Median Mean 3rd Qu. Max. 459.9 802.3 991.6 1066.0 1242.0 2382.0 I need to compute the sum of the values times their probability of occurence. The graph is fine, den <- density(cap, from=min(cap), to=max(cap), give.Rkern=F)