similar to: truncated normal

Suppose i want to compute a 95% highest density for a beta distribution beta(a,b) the two end points x1 and x2 shoudl satisfy the following two equations: pbeta(x1,a,b)-pbeta(x2,a,b)=95% dbeta(x1,a,b)=dbeta(x2,a,b) Is there any fast way to compute x1 and x2 in R? [[alternative HTML version deleted]]

Hello, I am a new user of R and found the function dtnorm() in the package msm. My problem now is, that it is not possible for me to get the mean and sd out of a sample when I want a left-truncated normal distribution starting at "0". fitdistr(x,dtnorm, start=list(mean=0, sd=1)) returns the error message "Fehler in "[<-"(`*tmp*`, x >= lower & x <= upper,

Does anyone know of an R-function that will generate an observation from a truncated normal (left or right) with a mu and sigma2? Any correspondence would be greatly appreciated. Best regards, Scott Summerill FAA ACB-330 SIGNAL Corp. 609-485-6377 scott.ctr.summerill at tc.faa.gov -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi, All, I have an n by m matrix with each entry between 1 and 15000. I want to know the frequency of each pair in 1:15000 that occur together in rows. So for example, if the matrix is 2 5 1 6 1 7 8 2 3 7 6 2 9 8 5 7 Pair (2,6) (un-ordered) occurs together in rows 1 and 3. I want to return the value 2 for this pair as well as that for all pairs. Is there a fast way to do this avoiding loops?

Hi, everyone, I need to use a C library. But since I have little experience in C, I want to call this C library in R and program the rest in R. Does anyone know how to do this? Thanks, Cindy [[alternative HTML version deleted]]

Hi, All, If I have a symmetric matrix, how can I get the negative square root of the matrx, ie. X^(-1/2) ? Thanks, Cindy [[alternative HTML version deleted]]

Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? Thank you, Cindy [[alternative HTML

Hi, I have a very basic question about install packages from CRAN on unix. I only installed on Windows before. Should I use the command install.package? The error message I got is syntax error near unexpected token `"mvtnorm"' Is it because I didn't set the path? Which path should I specify? Thanks, Cindy [[alternative HTML version deleted]]

Hi, All, I want to fit a normal mixture model. Which package in R is best for this? I was using the package 'mixdist', but I need to group the data into groups before fitting model, and different groupings seem to lead to different results. What other package can I use which is stable? And are there packages that can automatically determine the number of components? Thank you, Cindy

Hi, I have a R package, which is a .tar.tar file. And it is said to be source code for all platforms. And the author said it should install on any system (but he didn't know about Windows). I am wondering if I can use this package in Windows R. Thank you, Cindy [[alternative HTML version deleted]]

Hi, All, I have a density function with 3 variables which is defined on some irregular domain, and I want to get the marginal distribution of each variable. Is there any function doing this? A simple example is p(x,y,z)=x*y*z*I(xy>z). So each marginal distribution is a function of the other two variables. My density form is very complicated, so I cannot do it by hand. I was just wondering if

Hello, everyone, I have a matrix like following: school value A .1 A .2 A .15 A .2 B .3 B .5 C .3 C .3 C .4 C .5 C .6 C .9 C 1 I want to get the mean 'value' for each 'school', but each school has different length. Is there any way to do this fast? Because my

Hi, I want to plot the residuals of a least-squares regression. plot(lm(y~x), which=1) does this, but it plots the y-axis of my data on the x-axis of the residuals plot. That is, it plots the residual for each y-value in the data. Can I instead use the x-axis of my data as the x-axis of the residuals plot, showing the residual for a given x? Thanks! Jason Priem University of North

> x <- runif(100) > y <- runif(100) > ks.test(x,y) Two-sample Kolmogorov-Smirnov test data: x and y D = 0.11, p-value = 0.5806 alternative hypothesis: two-sided ok I expected that, but: > ks.test(runif(100), "runif") One-sample Kolmogorov-Smirnov test data: runif(100) D = 0.9106, p-value < 2.2e-16 alternative hypothesis: two-sided How

Dear List: I am trying to find the area between two ECDFs. I am examining the gap in performance between two groups, males and females on a student achievement test in math, which is a continuous metric. I start by creating a subset of the dataframe male<-subset(datafile, female="Male") female<-subset(datafile, female="Female") I then plot the two CDFs via

Hi, I'm Sorry for any cross-posting. I've reviewed the archives and could not find an exact answer to my question below. I'm trying to generate very large sparse matrices (< 1% non-zero entries per row). I have a sparse matrix function below which works well until the row/col count exceeds 10,000. This is being run on a machine with 32G memory: sparse_matrix <-

Dear List, I am trying to fit Truncated Lognormal to a data set that is 'truncated' from above a certain value, say, 0.01. Below is what I was able to come up with. I would appreciate it if you could review and make any necessary changes. # This is modified off the code for 'dtnorm' of library(msm). dtlnorm <- function (n, mean = 0, sd = 1, lower = -Inf, upper = Inf) {

I would like to generate pseudo-random numbers between two numbers using R, up to a given distribution, for instance, rnorm. That is something like rnorm(HowMany,Min,Max,mean,sd) over rnorm(HowMany,mean,sd). I am wondering if dnorm(runif(HowMany, Min, Max), mean, sd) is good. Any idea? Thanks. -james

http://r.789695.n4.nabble.com/file/n3567636/ecdfs.jpg ecdfs.jpg http://r.789695.n4.nabble.com/file/n3567636/ecdf_curve.gif ecdf_curve.gif Hello, I have generated a plot of two empirical CDFs (attachment 1). As a result, they are stepwise when plotted. The following code was used: > plot(ecdf(mut), do.points=FALSE, verticals=TRUE, xlim=range(mut, non), > col="red") >

Hello all, I have two columns of numbers. I would like to do the following: (1) Plot both cdfs, F1 and F2 on the same graph. (2) Find smoothed approximations of F1 and F2 lets call them F1hat and F2hat (3) Find values for F1hat when we substitue a value of x in it. (4) Find the corresponding densities of the cdfs. Any ideas? -- Thanks, Jim. [[alternative HTML version deleted]]