similar to: lookup function for density(...) objects

Thanks to Ross Ihaka and Bob Wheeler for responding to my earlier question. I looked into the Johnson system functions in SuppDists package. For now, I want to stick with the density(...) estimator, and so still need the variate lookup function. As per Ross' suggestion, I just did a numerical integration on the density object and used approxfun/splinefun to "lookup" the variate

Dear friends: It's possible make a legend in the coplot output? My data are: "dados"<-structure (list ( Qu1 = c(1,2,3,4,5,6,7,8,3,2), Qu2 = c(3,4,5,6,7,8,9,9,6,3), Ku1 = structure (factor ( c(1,1,1,1,2,1,2,2,1,1),levels=1:2),.Label=c("Kmin","Kmax")), Ph1 = structure (factor (

I'm interested if anyone can help me to the R to display multiple data elements on one graph - just a simple graph, nothing fancy. I can't seem to find an example of this. An example of what I'm looking for is, say, a CPU graph which graphs user, system, and idle time as a cumulative stack representing each data element as a different color. See the following URL for an example

I am using R1.2.0 on Windows NT4.0 and am looking for information on drawing geographical maps. [The things I'd like to do at the moment are rather simple, just like plotting the values of some variable (e.g. a SMR) on a given map.] Searching the r-help mailing list archives, it seems this topic comes up from time to time. For example, in November 1999 Ray Brownrigg writes about an "R

Dear friends, I try to get started with R and can’t estimate kurtosis of a random sample by using one command. I have installed R 1.6.2. Please help. Max --------------------------------- ur needs [[alternate HTML version deleted]]

Dear All, I have been trying to to do this for a few days now. I can generate persp plot OK and can generate it in colour using the command persp(x,y,z,col=terrain.colors(20)) However, I was wondering if it is possible to shade the 3d surface like a contour plot. i.e. black for large z, white for small z, say Thanks in advance Colin

At present R has separate functions "spline" and "splinefun". The first of these carries out spline interpolation of a data set and returns the interpolated values; the second returns the interpolating function itself (approx and approxfun are similar). I would like to combine these into a single function "spline" with an (optional) argument which determines which

Hello, is the following somehow possible with Mod() being a primitive: "Mod" <- function(x) UseMethod("Mod") "Mod.default" <- function(x) { .Primitive("Mod") ### I know it?s wrong. How can I access the original Mod ? } Thanks for help M. Eger -- +------------------------------------------------------- | Marcus Eger | Philipps Universitaet

Hello all, I'm using R1.2.2 and wonder whether there is already a new (unofficial) version that supports fill patterns for polygon(). thanks M.E. -- +------------------------------------------------------- | Marcus Eger +-------- ><> ------------------------------------------- | E-Mail: eger.m at gmx.de (NEW) | marcus.eger at physik.uni-marburg.de (OLD) | WWW:

Running R 1.2.3, Windows 98 I checked the archives, and I couldn't find anything pertaining to this: How do I control format (scientific notation versus decimal, e.g.) on tick labels? TIA, Henry Dr. M. Henry H. Stevens Postdoctoral Associate Department of Ecology, Evolution, & Natural Resources 14 College Farm Road Cook College, Rutgers University New Brunswick, NJ 08901-8551 email:

I've tried to move objects from S to R. In S+, I use data.dump() and data.restore(). I've made a file all.dum using data.dump(ls()) in S+, but the R command load("all.dum") gives an error: > load("/jaz/all.dum") Error: restore file corrupted -- no data loaded Is there any way to pass my objects from S+ to R? Thanks Agus Dr. Agustin Lobo Instituto de Ciencias de

Suppose I have two var x and y,now I want to fits a natural cubic spline in x to y,at the same time create new var containing the smoothed values of y. How can I get it?

I'd like to make some polar plots with R, but I can't seem to find anything designed to help with that. Is there anyway to get a real polar mode, where instead of x and y you have r and theta? How about a way to draw a circle? -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

thanks to all for the 2d scatter plot. i have one more. how do i plot 'hist(y1, col="red") and hist(y2,col="blue") in the same window? thanks again.

Hello! Please, anybody help me. Can I calculate area of density was created by: > D <- density(x) In other words I want to know area under curve 'plot(D)' and It's good to calculate area before and after 0 separately. -- View this message in context: http://www.nabble.com/Area-of-density-tp19338958p19338958.html Sent from the R help mailing list archive at Nabble.com.

I have been using the ECDF function in the Hmisc package to produce cumulative distribution function plots. The problem is that for small datasets the steps "look bad" (not my characterization but from the client). Is there a way to get the same information but smoothed? I have tried the densityplot (lattice), which gives a smoothed line, but this does not give the cumulative density.

Hi there, Sorry if this is a rather loing post. I have a simple list of single feature data points from which I would like to generate a probability that an unseen point comes from the same distribution. To do this I am trying to estimate the probability density of the list of points and use this to generate a probability for the new unseen points. I have managed to use the R density function to

Hi folks, I know that density function will give a estimated density for a give dataset. Now from that I want to have a percentage estimation for a certain range. For examle: > y = density(c(-20,rep(0,98),20)) > plot(y, xlim=c(-4,4)) Now if I want to know the percentage of data lying in (-20,2). Basically it should be the area of the curve from -20 to 2. Anybody knows a simple

I have done a re-working of the time series code in base R and library ts that will appear in Friday's snapshot. I am sure at least one person will be dissatisfied, but I am convinced there are fewer errors than there were before (I found more than 20, as well as several documented features that did not exist.) The principles in the code are: tsp attributes can only go on vectors of length

On 3/11/2018 3:35 PM, Christofer Bogaso wrote: > But for my reporting purpose, I need to generate a bell curve like > plot based on empirical PDF, that also contains original points. > > Any idea would be helpful. Thanks, > Christofer, something like the following may get you what you want: ## get the kernel density estimate dens <- density(Dat) ## estimate the density at