similar to: how to estimate conditional density

Hi, there. Suppose I have a bivarariate data matrix y1 and y2. I want to plot a 3-D picture of the estimated density f(y1, y2) against y1 and y2? How can I do that? Do I use persp() or density()? Thanks for your help. Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 1586 Murfin Ave. Apt 37 Ann Arbor, MI 48105-3135 yuleih at umich.edu 734-647-0305(H) 734-763-0421(O) 734-763-0427(O)

Hi, there. Can I ask how to set up missing values in R? Suppose I want to assign the missing value to the elements in vector which is greater than zero like this: x<-c(1,3,-1,0,4); after the missing value assignment, x becomes (NA,NA,-1,0,NA). Thanks! Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 1586 Murfin Ave. Apt 37 Ann Arbor, MI 48105-3135 yuleih at umich.edu

Hi, there. Does anybody know how to plot a smooth density plot for some data simulated from certain distribution? Thanks. Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 1586 Murfin Ave. Apt 37 Ann Arbor, MI 48105-3135 yuleih at umich.edu 734-647-0305(H) 734-763-0421(O) 734-763-0427(O) 734-764-8263(fax) $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Hi, there. I have two questions about the diagnostics in multivarite statistics. 1. Is there any diagnostics tool to check if a multivariate sample is from multivariate normal distribution? If there is one, is there any function doing it in R? 2. Is there any function of testing if two multivariate distribution are same, i.e. the multivariate extension of Kolomogrov-Smirnov test? Thanks for

Hi, there. Is there any function in R to plot the probability-probability plot (PP plot)? Suppose I am testing some data against normal. Thanks. Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 1586 Murfin Ave. Apt 37 Ann Arbor, MI 48105-3135 yuleih at umich.edu 734-647-0305(H) 734-763-0421(O) 734-763-0427(O) 734-764-8263(fax) $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Dear all: I am using R to do multiple imputation for longitudinal data set. The Gibbs chain basically requires draw posterior distribution of model parameters, including the random effects. The multiple imputation requires several independent Gibbs chains. So my program structure is like: for (chain in 1:5) { # perform Gibbs sampling... for (row in 1:row.no) { b.row=some function # draw

Hi, there. I have two questions about using R to create boxplots. 1. The function boxplot() plots the outliers. How can I label the exact values arount these outlier points? Does R have an option allow me to do that? 2. How can I put two boxplots in one x-y axis? Thanks. Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 276 Grove St. Apt 3 Newton, MA 02466 617-796-7834(H)

Estimate region of highest probabilty density Dear R-community I have data consisting of x and y. To each pair (x,y) a z value (weight) is assigned. With kde2d I can estimate the densities on a regular grid and based on this make a contour plot (not considering the z-values). According to an earlier post in the list I adjusted the kde2d to kde2d.weighted (see code below) to estimate the

Hi, there. Suppose I already have sensitivities and specificities. What is the quick R-function to calculate AUC for the ROC plot? There seem to be many R functions to calculate AUC. Thanks. Yulei [[alternative HTML version deleted]]

Hello, I am a little bit confused regarding the density values obtained from the function kde2d() from the package MASS because the are not in the intervall [0,1] as I would expect them to be. Here is an example: x <- c(0.0036,0.0088,0.0042,0.0022,-0.0013,0.0007,0.0028,-0.0028,0.0019,0.0026,-0.0029,-0.0081,-0.0024,0.0090,0.0088,0.0038,0.0022,0.0068,0.0089,-0.0015,-0.0062,0.0066) y <-

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

Problem: Based on a n x 2 data matrix i want a kernel estimate of the bivariate density. However, i also wish to specify wich points the density should be calculated at. I can offcourse just write the full kernel density estimate as a R-code, but surely there must already exist some package for this operation? The package density(), seems to create a new matrix (depending on n), where the

Hi, there. Does anyone know the R function for calculating the cdf of bivariate normal distribution function? Thanks. Yulei [[alternative HTML version deleted]]

Hi, there: Could someone tell me a simple function of plot ROC curve and calculate AUC in R? My setting is very simple, a column of the true binary response and another column of predicted probabilities. Thanks! Yulei [[alternative HTML version deleted]]

Hi, there: Suppose I want create variables with indexes in their names, e.g., X_1_1, X_1_2, X_1_3, ..., X_1_10, X_2_1, X_2_2, X_2_3, .. X_2_10,..., X_10_1, X_10_2, ... X_10_10. It looks like I need to use 2 indexes I and J so I is looped from 1 to 10, and J is looped from 1 to 10. But I don't know how to automatically produce X with these combination of indexes. Should I use paste function?

Hi all, I'm fairly new to R, so I'm still trying to feel out what is available to me. I would like to be able to plot joint density in a two dimensional plot where density is indicated by color or darkness gradients, like a 2d color coded topographic map. Ideally, the output would be something I could then plot other points or lines on. Currently, I'm calculating joint density with

Dear all, Please, look at the following code: attach(geyser) f1 <- kde2d(duration, waiting, n = 5) a <- 0 for (i in 1:5){ for (j in 1:5){ a <- a + f1$z[i,j] } } As far as I understood from Help kde2d returns matrix elements of which are values of joint probability mass function Pr(X=x,Y=y) therefore, sum of its elements should sum to 1. Which is not the case from my check. Where is

Hi, there: Does anyone know how to specify the ranges in the axises when I make scatter plots using pairs()? In the general plot function, I can use xlim and ylim option. But how can I do this if I use pairs()? Thanks. Yulei [[alternative HTML version deleted]]

Hi, there. How do I calculate the cross-product in the form of \sum_{i=1}^{n}X_{i}^{t} \Sigma X_{i} using R code without using do loop? X_{i} is the covariate matrix for subject I, \Sigma is the covariance matrix. Thanks for your help. Yulei [[alternative HTML version deleted]]

Hi, there: I have a dataset with 50 states and for each state, I have its associated mean estimate (for some parameters) and the lower and upper bound of the 95% CI. The data look like below: state ami_mean ami_low ami_up 1 MS -0.58630 -0.90720 -0.29580 2 KY -0.48100 -0.75990 -0.19470 3 FL -0.47900 -0.62930 -0.32130 I would like to have a plot the 95% CI (characterized by