similar to: How to generate the random numbers uniformly distributed on the unit disc?

>>>>> "VW" == Viechtbauer Wolfgang (STAT) <Wolfgang.Viechtbauer at STAT.unimaas.nl> >>>>> on Fri, 26 Sep 2008 18:00:19 +0200 writes: VW> Hi all, I'm trying to fit a marginal (longitudinal) VW> model with an exponential serial correlation function to VW> the Orange tree data set. However, R crashes frequently VW>

Dear all: I would like to create a landscape of environmental values that follow a uniform frequency distribution and also have spatial autocorrelation in the landscape. I was wondering if there is an algorithm and/or package out there that creates autocorrelation of values that are distributed according to a non-normal frequency distribution. Any suggestions are greatly appreciated. Thank you,

I wish to generate 100 by 1 vector of x1 and x2 both are uniform distributed with covariance matrix \Sigma. Thanks, Michael [[alternative HTML version deleted]]

I'm a beginner of R. I can use runif() to generate uniformly distributed numbers, but I don't know which function can generate uniformly distributed random integers, or what kind of method do? Thanks! -- View this message in context: http://www.nabble.com/how-to-generate-uniformly-distributed-random-integers-tf4960778.html#a14208376 Sent from the R help mailing list archive at

Hi, I would like to draw 10 uniformly distributed sample points from a circle with redius one and centered at (0,0). Is there any R function to do that?   Thanks, [[alternative HTML version deleted]]

Dear R users, I want to generate two random variables (X1, X2) from uniform distribution (-0.5, 0.5) with a specified correlation coefficient r. Does anyone know how to do it in R? Many thanks! Menghui

Dear ExpeRts, I am trying to plot a bunch of growth curves and would like to get some more control over groups and line colors than I seem to have. Example: # make some data dat <- Orange dat$group <- ifelse(dat$Tree%in%c('1','4','5'), 'A', 'B') # plot xyplot(circumference~age, dat, groups=group) # now use lines to make the growth curve more

Working with the built in R data set Orange, e.g. with(Orange, table(age, circumference)). How should I go about about grouping the ages and circumferences in the following ranges and having them display as such in a table? age range: 118 - 664 1004 - 1372 1582 circumference range: 30-58 62- 115 120-142 145-177 179-214 Thanks for any feedback and insights, as I hoping for an output that

Hi, I'd like to use Latin Hypercube Sampling (LHC) in the the context of uncertainty / sensitivity analysis of a complex model with approximately 10 input variables. With the LHC approach I'd like to generate parameter combinations for my model input variables. Therefore I came across an simple example here on the mailing list (

Hi folks, I am tearing my hair out on this one. I am using an example from Pinheiro and Bates. ### this works data(Orange) mod.lis <- nlsList(circumference ~ SSlogis(age, Asymp, xmid, scal), data=Orange ) ### This works mod <- nlme(circumference ~ SSlogis(age, Asymp, xmid, scal), data=Orange, fixed = Asymp + xmid + scal ~ 1, start =

I wish to generate a vector of uniformly distributed data with a defined correlation to another vector The only function I have been able to find doing something similar is corgen from the library ecodist. The following code generates data with the desired correlation to the vector x but the resulting vector y is normal and not uniform distributed library(ecodist) x <- runif(10^5) y

I am trying to generate two dimensional random coordinates. For randomly distributed data I have simply used >xy<-cbind(runif(100),runif(100)) However I also want to generate coordinates that are more uniformly distributed, and coordinates that are more contagiously distributed than the above. Can anyone make any suggestions Thanks. Dr Terry Beutel Rangeland Scientist Animal

Hello, I have a bunch of files containing 300 data points each with values from 0 to 1 which also sum to 1 (I don't think the last element is relevant though). In addition, each data point is annotated as an "a" or a "b". I would like to know in which files (if any) the data is uniformly distributed. I used Google and found out that a Kolmogorov-Smirnov or a Chi-square

On Nov 12, 2013, at 1:28 PM, Chandler Carruth <chandlerc at google.com> wrote: > On Mon, Nov 11, 2013 at 11:29 PM, Chris Lattner <clattner at apple.com> wrote: > Hi Manman (and llvmdev), > > I filed these two bugs to track the ideas that I was cooking: > > http://llvm.org/bugs/show_bug.cgi?id=17891 > http://llvm.org/bugs/show_bug.cgi?id=17892 > > TL;DR:

On Tue, Nov 12, 2013 at 4:14 PM, Chris Lattner <clattner at apple.com> wrote: > I'm moderately opposed to just encoding these in a string format. I think > we can do something substantially better both for space, time, and > readability. Fundamentally, there is no reason for the original metadata > node you describe to not *encode* its operands into a dense bit-packed blob

> > I might as well add to the offtopic thread... why are natuical miles longer than "regular" miles? Andrew A nautical mile is 1 minute of latitude. -------------- next part -------------- An HTML attachment was scrubbed... URL: http://lists.digium.com/pipermail/asterisk-users/attachments/20040112/6658a905/attachment.htm

Hello, I want to be able to make a plot that has several series with different color and linetype. Online documentation suggest that this is possible, but I haven't found how: "We can also create redundant mappings, mapping the same variable to multiple aesthetics. This is most useful when producing a graphic for both colour and black and white display." Here's what I have to

Dear all, How to obtain the odds ratio (OR) and 95% confidence interval (CI) with 1 standard deviation (SD) change of a continuous variable in logistic regression? for example, to investigate the risk of obesity for stroke. I choose the happening of stroke (positive) as the dependent variable, and waist circumference as an independent variable. Then I wanna to obtain the OR and 95% CI with

Hello Everyone, I have three variables: Waist circumference (WC), serum triglyceride (TG) level and gender. Waist circumference and serum triglyceride is numeric and gender (male and female) is categorical. From these three variables, I want to calculate the "Lipid Accumulation Product (LAP) Index". The equation to calculate LAP is different for male and females. I am giving both

Dear Mr. Savicky, I am currently working on a project where I want to test a random number generator, which is supposed to create 10.000 continuously uniformly distributed random numbers between 0 and 1. I am now wondering if I can use the Chi-Squared-Test to solve this problem or if the Kolmogorov-Smirnov-test would be a better fit. I came across one of your threads on the internet where you