similar to: function 'density' in r-devel

Hi, in last nights alpha version, `var' is broken: R> var(rnorm(100)) Error in var(rnorm(100)) : 3 arguments passed to "cov" which requires 4. which I suspect is due to recent changes to `cov'. The same is true for R> cov(rnorm(100), rnorm(100)) Error in cov(rnorm(100), rnorm(100)) : 3 arguments passed to "cov" which requires 4. Best, Torsten R> version

Ben Bolstad experienced something odd while running R CMD check over a package of ours using r-devel (yesterday's fresh). He tracked down the problem to a vignette calling 'library(MASS)'. Please kindly ignore if this is a known (and temporary) issue. Laurent ----- Forwarded message from Ben Bolstad <bolstad@stat.berkeley.edu> ----- Return-Path:

sorry for cross-posting Dear all, I have tow (several) bivariate distributions with a known mean and variance-covariance structure (hence a known density function) that I would like to compare in order to get an intersect that tells me something about "how different" these distributions are (as t-statistics for univariate distributions). In order to visualize what I mean hear a little

I have run the following logistic regression model: options(contrasts=c("contr.treatment", "contr.poly")) m <- glm(wolf.cross ~ null.cross + feature, family = "binomial") where: wolf.cross = likelihood of wolves crossing a linear feature null.cross = proportion of random paths that crossed a linear feature feature = CATEGORY of linear feature with 5 levels:

I am experiencing strange results using dmvnorm. I define a scaled distance matrix from the coordinates bellow and then calculate a covariance matrix using a spherical correlation function. Then with certain combinations of range and sill parameters dmvnorm is returning values greater than 1. Surely the results of dmvnorm should be in the interval 0:1 (or do I just nead a holiday?). In addition

Hi, I try to compute critical value for multivariate normal distribution, and I find the crit(fit, const = c(0, 1), d = 1, cov = 0.95, rdf = 0) which seems to compute critical value. However, I can't compute right critical value for multivariate normal distribution which I want. I don't know how to solve my question. I send my question in the file. Would you help me to solve it, please?

Thank you for doing this. The size issue is actually a big concern for me. So this is step in the right direction. Two other points to consider, that would help us: 1) When using -fcoverage-mapping, some of the information is emitted in the text section. This is creating linking issues with very large files. It does not seem any of this information should necessarily be in the text

Dear All: I tried to replicate a case study described by Prof. Harrell in Chapter 7 of his Regression Modeling Strategies book, but failed on using anova.Design to reproduce his table 7.1, Following is the code: rm(list=ls()) library(Hmisc) library(Design) getHdata(counties) counties$older <- counties$age6574 + counties$age75 label(counties$older) <- '% age >= 65, 1990'

Greetings R users, I am an R graphics newbie trying to produce a custom trellis plot using pairs() with R 2.7.2. I have spatial data on which I run a geographically weighted regression (gwr, using the -spgwr- package). I want to check the gwr coefficients for multicollinearity and spatial association, following Wheeler and Tiefelsdorf (2005), and I would like to summarize the results of this

Dear all, I had to extracts/set elements from/in a matrix. Let say I have two vectors dim1 and dim2 of indices in the respective two dimensions of a matrix: I want to extract all the corresponding elements. I the case of a nxn matrix, dim1 <- 1:n and dim2 <- 1:n would extract the diagonal. I know one way would be to use the functions 'row' and 'col', but the matrixes I

Hello, I have a vector {a, b1, b2, b3, b4}. How can I calculate the following matrix: var(a) cov(a, b1) cov(a, b2) cov(a, b3) cov(a, b4) cov(a, b1) var(b1) cov(a, b2) cov(a, b3) cov(a, b4) ... ... cov(a, b1) cov(a, b2) cov(a, b3) cov(a, b4) var(b4) I would very appreciate your inputs. Thank you very much. Sincerely, Jialin Huang [[alternative HTML version deleted]]

Dear Mr. Therneau, Mr. Fox, or to whoever, who has some time... I don't find a solution to use the "survfit" function (package: survival) for a defined pattern of covariates with a Cox-Model including a time dependent interaction term. Somehow the definition of my "newdata" argument seems to be erroneous. I already googled the problem, found many persons having the

Dear R community Have just recently got back into R after a long break and have been amazed at how much it has grown, and how active the list is! Thank you so much to all those who contribute to this amazing project. My question: I am trying to calculate Mahalanobis distances for a matrix called "fgmatrix" >dim(fgmatrix) [1] 76 15 >fg.cov <- cov.wt(fgmatrix)

On Mon, Jun 10, 2019 at 2:11 PM <vsk at apple.com> wrote: > > > On Jun 6, 2019, at 9:56 AM, Nico Weber <thakis at chromium.org> wrote: > > On Wed, Jun 5, 2019 at 1:33 PM <vsk at apple.com> wrote: > >> >> >> On Jun 4, 2019, at 4:41 PM, Nico Weber <thakis at chromium.org> wrote: >> >> On Mon, Jun 3, 2019 at 2:06 PM <vsk at

rkotler at mipsswbrd006-le:~/caviumllvm/build/test$ make Making LLVM 'lit.site.cfg' file... Making LLVM unittest 'lit.site.cfg' file... ( ulimit -t 600 ; ulimit -d 512000 ; ulimit -m 512000 ; ulimit -s 8192 ; \ /usr/bin/python /home/rkotler/workspace/llvm/utils/lit/lit.py -s -v . ) XPASS: LLVM :: tools/llvm-cov/llvm-cov.test (8916 of 9784) ******************** TEST

Hi, I have the following problem: I have a data.frame with 36 sample sites (colums) for which I have covariates in 3 categories: Area, Month and River. Each Area consists of 3 rivers, which were sampled over 3 month. Now I want to fuse River 1-3 for one area in one month. To get a data.frame with 12 colums. I am trying to do a "for loop" (which may be a complicated solution, but I

Dear list, what is the fastest way to compute a multivariate mean and cov-matrix? I presume that the mean is computed in cov, so it may be a waste of time to compute the mean first and then a second time inside of cov. Is it faster to use cov.wt, which gives cov-matrix and center? And: If mean and cov should be computed on a part of the data, is it faster to use cov.wt with some weights zero, or

Hi all, I want to get results for cox proportional hazards on SNP data. I'm trying to get HRs, CI's, & p-values for each individual SNP - this is represented by cov[,i]. When I run my code, I get the following error: subscript out of bounds. I don't know why I am getting this error. I have looked through the R logs, but nothing that has been previously suggested has helped so

Hi, Excuse me for asking this silly question. But I really couldn't understand why cov() and ccov() don't work for my calculation of covariance matrix. a <- matrix(1:8, 2, 4) a [,1] [,2] [,3] [,4] [1,] 1 3 5 7 [2,] 2 4 6 8 > ccov(a) Error in solve.default(cov, ...) : Lapack routine dgesv: system is exactly singular I also tried colume bind, but it

Hi dear list, I'm scrambling with this: i have a p-dimensional data frame for which i want to have a pairs() plot, with ellipse added in each lower.panel. I want the ellipse's parameter (mu, sigma) to be extracted from the appropriate entries in a pre-computed matrix ("dab" in the code below). Can it be done ? Thanks in advance, melly<-function (x, y, col =