similar to: bivariate normal distribution

Dear R-help list members, I have created a package 'mnormt' with facilities for the multivariate normal and t distributions. The core part is simply an interface to Fortran routines by Alan Genz for computing the integral of two densities over rectangular regions, using an adaptive integration method. Other R functions compute densities and generate random numbers. The starting

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

[Hope this is the right list where to send...] An attempt to update package 'mnormt' involves the addition of a small new function called 'pd.solve'. When I come to the package checking stage, an error occurs in parsing pd.solve.Rd. The full transcript of the outcome is copied below (it includes details on my installation) but the critical point is where the \examples{} section

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. 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]]

Hi. I'm trying to take a data set with two independent and one dependent variable and enter a x,y value to predict the dependent with a nonparametric technique. I've been using interpp in the akima package, (windows xp, R 2.4.1), but get values that are orders of magnitude off when the predictors are slightly out of the range of the data set. Can you recommend a function for me?

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, 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: 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

Hi, I've estimated a simple kernel density of a univariate variable with density(), but after I would like to find out the CDF at specific values. How can I do it? thanks for your help, with it I am very close to finish my first little bit more serious work in R, Viktor

Hi, there. Suppose I have a bivariate data set y1 and y2. Can anybody tell me how to estimate the conditional density of f(y1|y2) and vice versa? Thanks. Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 1586 Murfin Ave. Apt 37 Ann Arbor, MI 48105-3135 yuleih at umich.edu 734-647-0305(H) 734-763-0421(O) 734-763-0427(O) 734-764-8263(fax) $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

I have written the following function to calculate the weighted mean difference for univariate data (see http://www.xycoon.com/gini_mean_difference.htm for a related formula). Unsurprisingly, the function is slow (compared to sd or mad) for long vectors. I wonder if there's a way to make the function faster, short of creating an external C function. Thanks very much for your advice. gmd

In the document "R Data Import/Export", section "Output to connections", there is the following portion of code: ## convert decimal point to comma in output, using a pipe (Unix) zz <- pipe(paste("sed s/\\./,/ >", "outfile"), "w") cat(format(round(rnorm(100), 4)), sep = "\n", file = zz) close(zz) ## now look at the output

There seems to exist peculiar cases where optim does not take care of constraints on the parameters to be optimized over. The call to optim is of the form opt <- optim(cp, fn=sn.dev, gr=sn.dev.gh, method="L-BFGS-B", lower=c(-Inf, 1e-10, -0.99527), upper=c( Inf, Inf, 0.99527), control=control, X=X, y=y, hessian=FALSE) The code has worked fine

I have justed upgraded R v1.7.0 on Windows NT 4 and have installed the latest RMySQL (version 0.5-1)and DBI (version 0.1-5) packages. When I issue the following commands (tactfully adjusted) R just crashes and disappears, any ideas? require(RMySQL) m <- dbDriver("MySQL") con <- dbConnect(m, dbname="xxx", user="xxx", password="xxx",

Hi all, I'd like to quantize a variable to map it into a limited set of integers for use with a colormap. "image" and filled.contour" do this mapping inside somewhere, but I'd like to choose the colors for plotting a set of polygons. Is there a pre-existing function that does something like this well? i.e., is capable of using 'breaks'?

Hello, How can I obtain the likelihood ratio of a Poisson regression model? Regards. _____________________________________________ dr. Marziliano Ciro Facolta' di Economia Universita' degli Studi di L'Aquila p.zza del Santuario, 19 67040 Roio Poggio, L'Aquila tel.: 0862 434836 fax: 0862 434803

I am learning glm function, but how do you fit data using exponential distribution with glm? In the help file, under "Family Objects for Models", no ready made option seems available for the distribution as well as for other distributions satisfying GLM requirements not listed there.