similar to: plotting density for truncated distribution

Hi all, Do any packages implement density estimation in a modelling framework? I want to be able to do something like: dmodel <- density(~ a + b, data = mydata) predict(dmodel, newdata) This isn't how sm or KernSmooth or base density estimation works. Are there other packages that do density estimation? Or is there some reason that this is a bad idea. Hadley -- http://had.co.nz/

Hi folks: Is there a lookup function that returns the variate given the cumulative probability for an object returned by the density(...) function? > mydata _ as.vector(mymatrix) > mydata.density _ density(mydata) > mydata.p80 _ lookup(mydata.density, p=0.8) # is there any function to accomplish this task? Thanks. Rajiv. -------- Rajiv Prasad, Postdoctoral Research Associate,

Hello, I was wondering if I can plot two curves I get from "density(data)" into one plot. I want to compare both. With the following commad, I just get one curve plotted: plot( density(mydata) ) Sorry for this stupid question but I could not find a solution until now... Antje

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)

Hello R users, When I type d <- density(MyData$x) I obtain a density object I can plot, But I wonder if there is a way to easily compute the length of the density curve ? ( I imagine I could compute the distances between the 512 equally spaced points using their x and y, but does it exist a smarter way ?) Regards, SW

Hello R-community, I want to generate stacked density plots in lattice. My data consist of a numeric variable ('pid') that is measured in different individuals ('id'), which can be divided in two types ('type') and the measurements were repeated a different time points ('day'). I read in the Lattice book that this can be done using the 'flowViz'

Hi, Does anybody encounter the same problem when we overlap histogram and density     that the density line seem to shift to the right a little bit?           If you do have the same problem, what should we do to correct that?           Thank you.           par(mar=c(4,4,2,1.2),oma=c(0,0,0,0))     hist(datobs,prob=TRUE, main ="Volume of a catchment from four    

Ultimately my aim is to get a plot of density faceted by 2 factors with a horizontal boxplot overlaid on each density plot in the grid to indicate summary stats. So I've been experimenting with creating boxplots and density plots. Here's some representative data. series = c('C2','C4','C8','C10','C15','C20') ids =

How can I plot the graph of a density of a sample with an unknown distribution? I can provide any sample size which is required. I want to have a smooth density graph of my data. New Email addresses available on Yahoo! Get the Email name you&#39;ve always wanted on the new @ymail and @rocketmail. Hurry before someone else does! [[alternative HTML version deleted]]

Hello! Up to now I have been using hist() to display the distributions. Howevere, I noteiced strange numbers on y (vertical) axis, if I used probability = T or freq = F option. I thought it is a bug and launched the R-bug system and found some posts on that matter. Brian Ripley responded to one, that one should look at truehist() for that. Ok I can use truehist() if I want to see the ratios

Hello... Is it possible to use "density" or another kernel density estimator to identify the mode of a distribution? When I use 'density', the resulting density plot of my data is much cleaner than the original noisy histogram, and I can clearly see the signal that I am interested in. E.g., suppose my data is actually drawn from two or more normal (or other)

Hello, I am trying to compute the density of a variable k that is either (1) Normally distributed; (2) Log-Normally distributed; or (3) follows proportional error distribution. I tried to search R-help and the answer for normal distribution was easy to find (please see 1c). I am not sure if my formula for dlnorm is correct (please see 2c below)? I really don't know what function to use for the

Hi there, I am working on a project which needs the value of the interaction area under two distributions( eatimated by kernel density estimators). For example: x<-rnorm(100,0,1) y<-rnorm(100,0.2,1) density(x) # This produces the summary of dependent variable and independent variable. How can I get the individual values of variables and reform a curve to calculate the area under

Dear All, I am trying to visualize the surface of a bivariate kernel density estimate. I have a vector of bivariate observations(x,y), and a function which computes the kernel density estimate z corresponding to each observation. I cannot generate the (x,y) data in the ascending order needed by persp(x,y,z). I was wondering whether there is an R version of the S function interp. Would anybody

Dear R-list, I have a statistical problem with the comparison of short time-series, representing densities of fish in different streams. For each stream (6 in total, here below showed only part of the dataset) I have 8 years of density data, as follows: year density stream 1 2000 0.51 stream1 2 2001 0.87 stream1 3 2002 0.68 stream1 4 2003 0.56 stream1 5 2004 0.50 stream1 6

Dear List, I have an array of 6400 x 56 elements. I want to calculate the density function for each column and plot all 56 density functions in one plot. I have tried several procedures, but they all failed. What can I do? TIA Christian [[alternative HTML version deleted]]

I am trying to plot a lognormal density curve on top of an existing histogram. Can anybody suggest a simple way to do this? Even if someone could just explain how to plot a regular normal density curve on top of an existing histogram, it would be a big help. Also, is there some way to search through the R-help archives other than simple browsing? Thank you so much. Your help and time is greatly

Hi everyone, I am confused regarding the function "density". suppose that there is a sample x of 100 data points, and plot(density(x)) gives it's pdf ? or it's more like histogram only ? thanks for any answering Carrie [[alternative HTML version deleted]]

Am trying to do some study on bivariate binomial distribution. Anyone knows if there is package in R that I can use to calculate the density function of bivariate binomial distribution and to generate random samples of it. Thanks, -- View this message in context: http://n4.nabble.com/How-to-calculate-density-function-of-Bivariate-binomial-distribution-tp992002p992002.html Sent from the R help

Dear All, I have two questions regarding distribution fitting. I have several datasets, all left-truncated at x=1, that I am attempting to fit distributions to (lognormal, weibull and exponential). I had been using fitdistr in the MASS package as follows: fitdistr<-(x,"weibull") However, this does not take into consideration the truncation at x=1. I read another posting in this