similar to: Missing value in circ.mean and polar.plot

Hi, i found a bug in circ.plot of CircStats package, namely that the plot ingore the datasets with value = 0. it's simple to fix it, but i cannot seem to figure out where to submit the fix. is there a official procedure of submitting bug report/patch to the contributed packages? -- View this message in context:

I've just gotten through translating my notes for the course in basic statistics for health researchers. I've placed a copy on ftp://blueberry.kubism.ku.dk/priv/R-intro.tgz This is essentially a translation of the Danish notes that I wrote during the Autumn of 1997 for use with Rsept, i.e. roughly R v.50. They lean heavily on the textbook, Altman: Practical Statistics for Medical

I have a vector of dimension 67, but CircStat circ.summary and circ.disp seems to conclude that the dimension is 1. I am new to R so maybe I'm just missing something. > dim(data) [1] 67 1 > circ.mean(data) [1] 0.2200071 > circ.summary(data) n mean.dir rho 1 1 0.2200071 43.12534 > circ.disp(data) n r rbar var 1 1 43.12534 43.12534 -42.12534 >

Hello all, I am trying to use xyplot to give a six panel plot and to highlight only points (in any panel) that meet a certain criterion. With the plot command I would do something like: plot.default(filein$Site,filein$circ.conc) points(filein$Site,filein$circ.conc,type="p", pch=ifelse(filein$p.value<5e-02,19,21)) I had thought I could just stick in the pch line from above into

circ.plot in CircStats under R 1.8.0 yields incorrect plots (easily compare hist() and rose.diag()). However, the code in circ.plot has not changed. Has anyone tracked this down yet?

Hello, I am quite new to R and although I have read some material (apparently not enough) I'm getting very frustrated. I'm trying to do some simple circular statistics in R (CircStats, primarily circ.mean) and I'm confused about the results. What is a negative radian or degree mean in R? I thought it would be a coterminal angle, but that doesn't make sense with my data

Hello everyone, I'm stumped. I'd like to create a scatterplot matrix with circular reference lines. Here is an example in 2d: library(ellipse) set.seed(1) dat <- matrix(rnorm(300), ncol = 3) colnames(dat) <- c("X1", "X2", "X3") dat <- as.data.frame(dat) grps <- factor(rep(letters[1:4], 25)) panel.circ <- function(x, y, ...) { circ1

Hello, Once again, I posted a message without a subject line. Sorry.... here is the question again. Is there a simple way to modify the circ.mean function in the CircStats package to include a vector of weights to obtain a weighted average angle? Thanks! Martin -- Martin Biuw Sea Mammal Research Unit Gatty Marine Laboratory, University of St Andrews St Andrews, Fife KY16 8PA Scotland Ph:

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Anyone else using CFS on CentOS 4.4 ? I have started using it today (unimportant stuff for now, for testing), and am wondering what are other people experiences with it. I'm using version 1.4.1, rpms kindly provided by Karan on his repository. My main concern is data loss, not security itself. From what I noticed, the strenght of CFS crypto is

My % of packets lost vary usually in function of signal strenght. Since i cannot forecast the % of frames i will lost except with the criteria just said, could be a good approach to set the PLC tuning % dynamically during runtime basing it statistically on the number of ACKed frames? Does the % of frames lost include silence frames (6 bytes frames, i'm using VBR)? So do i need to consider

Hi people! I have a few problems with the password strength in Samba. I have a PDC with LDAP on Debian Stable, with a few packages from backports. The problem is that I can't find a way to enforce strenght to the passwords of the users. I can't define a policy to force things like: number of uppercase letters, number of downcase letters, number of numbers in the password, to check the

Hi- > I haven't seen a machine in which OR is faster than ADD nor more energy-efficient. They're all done by the same ALU circuitry which delays the pipeline by its worstcase path timing. So, for modern processor hardware purposes, OR is exactly equal ADD. Transforming ADD to OR isn't strenght reduction at all. Maybe this is benefical only if you have a backend generating circuitry

I agree the presentation needs work haha. That''s something I really haven''t put a lot of thought into yet. I''m hoping to start polishing it up after I get the first half edited and cleaned up text-wise. Since it seems everyone is interested in it, I can definitely post a summary and TOC; I had one up and then when I launched the new site I didn''t put it back

Hi, I've currently to work with some circular data. Unfortunately I'm not very familiar with circular statistics and would really appreciate if I could get some help concerning the CircStats package this way. My data lies in the range 0 to 2*pi, and is transformed to radians (as expected by the CircStats methods). Calculating the mean direction (circ.mean) results for some datasets in a

Hi, On Tue, Jul 26, 2011 at 11:32 AM, Matt Johnson <johnso87 at crhc.illinois.edu>wrote: > Hi Daniel, > > > Hi folks, > > > > I couldn't find a specific XOR (OR and AND) optimization on llvm, and > > therefore I am about to implement it. > > But first I would like to check with you guys that it really does not > exist. > > > > For a

Hello all, My question is how do I write a multilevel regression model of individual responses to environmental predictors that accounts for social interactions between individuals. i.e.; 1) Individual response is nested within a group response. 2) The same environmental predictors apply to both hierarchical levels but, 3) Lower level slope/intercept are also affected by high-level response.

I have a problem that deals with correlating wind velocity to seed collection data. The problem lies in that I have a wind data set that is contains 2000+ data points and weed collection data on the order of a couple hundred. Both data sets were collected for the same time period, but there is not a one-to-one wind velocity->seed location match. My understanding of correlation is that you

Hello all, I'm trying to create a heatmap using 2 matrices I have: z and v. Both matrices represent different correlations for the same independent variables. The problem I have is that I wish to have the values from matrix z to be represented by color intensity while having the values from matrix v to be represented by circle size. I currently have the following in front of me and an unsure

Josh Coalson wrote: >> Thus,... if I currently have my index-based wav files (that is EAC >> makes >> track-number.index-number.wav) from an cdda,.. and the corresponding >> CUE >> file (EAC writes it in min:sec:frame),... than I could use sox to >> concatenate the single files to one big file,.. >> encode it to flac with the CUE infos,.. >> And

Hello! I have a dataset with the following two vectors: year<-c(1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009)