similar to: Area of density

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,

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

Hi, I'm using the density() command for a given vector x and I would like to know how to get the estimated value of the density for each element of the vector x instead of values corresponding to points from a grid. Thanks Florent Bresson

The following is from version 1.6.2 of R under Windows, or 1.6.1 under Mac OSX/X11 > density(1) Error in if (!(lo <- min(hi, IQR(x)/1.34))) (lo <- hi) || (lo <- abs(x[1])) || : missing value where logical needed I am not sure how this should be handled. I encountered it in connection with densityplot(). In that connection, it might be enough to modify density() so that it

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

Hi, I have a vector 'data' of 58 probability values (bounded between 0 and 1) and want to draw a probability density function of these values. For this, I used the commands: data <- runif(58) a <- density(data, from=0, to=1) plot(a, type="l",lwd=3) But then, when I try to approximate the area under the plotted curve with the command: area <- sum(a$y)*(a$x[1]-a$y[2])

Hi there, I have two series of data. plotting the density function of both gives me an idea about the difference of the data. But I would like to quantify the difference I see. a <- rnorm(100) b <- rnorm(100) da <- density(a) db <- density(b) The problem is that da$x and db$x are different and so I have difficulties to compare them... Is there any way to force the density

Hi group, I am creating two density plots as shown in the code below: x1 <- c(1,4,5,3,2,3,4,5,6,5,4,3,2,1,1,1,2,3) x2 <- c(1,4,5,3,5,7,4,5,6,1,1,1,2,1,1,1,2,3) plot(density(x1, na.rm = TRUE)) polygon(density(x2, na.rm = TRUE), border="blue") How can I determine the area that is covered between the two plots as a number and how can I grey (or highlight with a pattern) the area

Dear R-listers, I have created a plot to display the density lines for the same variable by different entities. Now, I want to fill the area under the density lines with semitransparent colors. Though I have checked that in web-searching and book-reading, I still do not perform that. Could anyone please give me any helps or advice? Thank you in advance. The data and code I used listed below: #

Hello, I have a question regarding shading regions under curves to display 95% confidence intervals. I generated bootstrap results for the slope and intercept of a simple linear regression model using the following code (borrowed from JJ Faraway 2005): > attach(allposs.nine.d) > x<-model.matrix(~log(d.dist,10))[,-1] > bcoef<-matrix(0,1000,2) > for(i in 1:1000){ +

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

Hi, Thanks for your mail, and time It is not working for some arguments, when mean value is like >6. case mc0 <- c(0.08844446,0.1744455,0.1379778,0.1209769,0.1573065,0. 1134463,0.2074027) rv <-UnivarMixingDistribution(Norm(486.4255, 53.24133), Norm(664.0713, 3.674773), Norm(669.0484, 4.101381),

What is the correct syntax for finding the area under the standard normal density for a particular value of z? Thanks [[alternative HTML version deleted]]

Hi, we all know that R is powerful in dealing with graphics. I am now trying to use R to show some geographic attributes for a specific geographic area on a graph. For example, if I would like to generate a graph showing the population densities (in terms of the intensity of colors) for Illinois State by zip codes. I did some research; and it seems that package "maptools" is

Hi, Having a weird problem with the integrate function. I have a function which calculates a loss density: I'd like to integrate it to get the distribution. The loss density function is: lossdensity<-function(p,Beta,R=0.4){ # the second derivative of the PDF # p is the default probability of the pool at which we are evaluating the lossdensity # Beta is the correlation with the market

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, On Mon, Mar 12, 2018 at 3:49 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > You need to re-read ?density and perhaps think again -- or do some study -- > about how a (kernel) density estimate works. The points at

HI there, I have been trying to use a code posted on R help to be able to calculate area under the curve for complicated data points and there seems to be an issue with the code: no "b" object found. I am not a good R user and can''t find were the problem is. Any help? Thanks!! This is the code ( as a test run I gave it this info because I know the answer: x<-seq(1:50)

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 > > >

Dear Listers, I am drawing a plot of two density curves, for male and female incomes. I would like to shade/hatch/color (whatever) the areas under the curves which are distinctive for each gender. This is the code I have tried so far: m <- density(topmal.d$y, bw = "sj") f <- density(topfem.d$y, bw = "sj") par(mfrow = c(1,1)) plot(x = c(0,400), y = c(0,0.02), type =

Hello, I have this code to plot a certain normal distribution and represent the pnorm value for a certain "x": x<-300 xx <- seq(2.5,7.5, by=0.1) yy <- dnorm(xx,5.01,0.77) d<-signif(pnorm(log(x), 5.01,0.77),4) xpts <- round(exp(0:8)) par(bg = "antiquewhite") plot(xx,yy, type="l", col="blue", lwd=2, xaxt="n",