search for: prespecify

Hello I tried a few searches on hist, histogram, equidist and space (space=0 was mentioned in one contribution), but none of that so far worked. It also says in the help "##-- For non-equidistant breaks, counts should NOT be graphed unscaled:" - which is precisely what I am looking for, but I cannot find it. I want to make a histogram using breaks which are spaced exponentially and in

Suppose I have a list where I want to extract only the elements that occur in every component. For instance in the list foo I want to know that the numbers 2 and 3 occur in every component. The solution I have seems unnecessarily clunky. TIA, Andy foo <- list(x = 1:10, y=2:11, z=1:3) bar <-unlist(foo) bartab <- table(bar) as.numeric(names(bartab)[bartab==length(foo)])

I am trying to generate a fourth vector,z, given three known and fixed vectors, x1,x2,x3 with corresponding known and fixed correlations with themeselves and with z. That is, all correlations are known and prespecified. How can I do this? Thank you, ben

Hello all, Would somebody be kind enough to show me how to do a KS test in R for a lognormal distribution with ESTIMATED parameters. The R function ks.test()says "the parameters specified must be prespecified and not estimated from the data" Is there a way to correct this when one uses estimated data? Regards, Kwabena. -------------------------------------------- Kwabena Adusei-Poku

On 15 Jun 2004 at 13:52, Vito Muggeo wrote: > Dear Petr, > Probably I don't understand exactly what you are looking for. > > However your "plot(x,c(y,z))" suggests a broken-line model for the > response "c(y,x)" versus the variables x. Therefore you could estimate > a segmented model to obtain (different) slope (and breakpoint) > estimates. See

I have a data set with 6 variables and 251 cases. The people who supplied me with this data set believe that it falls naturally into three groups, and have given me a rule for determining group number from these 6 variables. If I do scaled.stuff <- scale(stuff, TRUE, c(...the design ranges...)) stuff.dist <- dist(scaled.stuff) stuff.hc <- hclust(stuff.dist)

Hello, How do I get plot.survfit to draw a survival curve with prespecified time periods, say 1 month, 2, months, 3 months, 6 months, 1 year, 2 years etc) instead of the individual times of all events? Sincerely Fredrik Lundgren

Greetings, I have a nagging problem with contrasts and I can't seem to resolve it. A factor exists with four levels (lib1, lib2, con1, con2) and when I check the contrasts or set the contrasts to any of the prespecified ones, I do not get the exact contrasts necessary to test the theoretically relevant ones. I need orthogonal contrasts that look just like this matrix: con1 con2

I'm trying to compute sample size requirements for a binomial exact test. we want to show that the proportion is at least 90% assuming that it is 95%, with 80% power so any asymptotic approximations are out of the questions. I was planning on using binom.test to perform the simple test against a prespecified value, but cannot find any functions for computing sample size. do any exist?

Dear list, I use R 1.3.0 on Solaris. Today I realized that the html help search engine does not work at the moment (this means that I always get the search engine page again if I try to specify a search word, and click "search" or one of the prespecified topics), presumably since the latest netscape update. Do you have an idea what can be wrong? Perhaps this must be fixed not by the

Version 2.0-0 of meta (an R package for meta-analysis) is now available on CRAN. Changes are described below. Yours, Guido Major revision R package meta linked to R package metafor by Wolfgang Viechtbauer to provide additional statistical methods, e.g. meta-regression and other estimates for tau-squared (REML, ...) New functions: - metareg (meta-regression) - metabias

Version 2.0-0 of meta (an R package for meta-analysis) is now available on CRAN. Changes are described below. Yours, Guido Major revision R package meta linked to R package metafor by Wolfgang Viechtbauer to provide additional statistical methods, e.g. meta-regression and other estimates for tau-squared (REML, ...) New functions: - metareg (meta-regression) - metabias

Hi all, I am trying to estimate few parameters using the constained maximum likelihood in R and more specifically the constOptim() from the stata package in R. I am programming in Python and using R via the RPy2. In my model, I am assuming that the data follow the Beta-distribution, so I created a simulated dataset by using prespecified values for the parameters and now I am trying to estimate

[Note to R. Wolff -- thanks for the pointers and the program. As I understand its workings, it would run as root and bind a listen port to a particular program -- with a list being supplied in /etc/portadmin or other file. Basically, a listen wrapper. Hopefully this message will address your cleanup concerns in my previous message. Thanks. Also, you may want to provide a moderator''s

Is there anyway to preset date formats? I have a date from a cover.dbf that is shown as this: > cover$FINALREPOR [1] "2003-06-24" The numeric value in cover$FINALREPOR is 12227. I'd rather not create another vector to hold the properly formatted date. When I put this in a WordPerfect merge, I want the date to be June 24, 2003. I could take care of the problem in a

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Dear R-users, One of the main reasons I moved from GAUSS to R (as an econometrician) was because of the existence of the library LOCFIT for local polynomial regression. While doing some checking between my former `GAUSS code' and my new `R code', I came to realize LOCFIT is not quite doing what I want. I wrote the following example script:

Hello R users, I've used the following help two compare two regression line slopes. Wanted to test if they differ significantly: Hi, I've made a research about how to compare two regression line slopes (of y versus x for 2 groups, "group" being a factor ) using R. I knew the method based on the following statement : t = (b1 - b2) / sb1,b2 where b1 and b2 are the two slope

Hello, I have a 32 GB RAM Mac Pro with a 2*2.4 GHz quad core processor and 2TB storage. Despite this having so much memory, I am not able to get R to utilize much more than 3 GBs. Some of my scripts take hours to run but I would think they would be much faster if more memory is utilized. How do I optimize the memory usage on R by my Mac Pro? Thank you! Kurinji [[alternative HTML version

-------- Original Message -------- Subject: Re: [R] Simulation - Natrual Selection Date: Wed, 05 Jan 2011 17:24:05 +0000 From: Ben Ward <benjamin.ward@bathspa.org> To: Bert Gunter <gunter.berton@gene.com> CC: Mike Marchywka <marchywka@hotmail.com> On 05/01/2011 17:08, Bert Gunter wrote: > Couple of brief comments inline below. -- Bert > > On Wed, Jan 5, 2011 at