similar to: Appending results via for loop

Displaying 20 results from an estimated 800 matches similar to: "Appending results via for loop"

2010 Feb 09
2
Double Integral Minimization Problem
Hello all, I am trying to minimize a function which contains a double integral, using "nlminb" for the minimization and "adapt" for the integral. The integral is over two variables (thita and radiusb) and the 3 free parameters I want to derive from the minimization are counts0, index and radius_eff. I have used both tasks in the past successfully but this is the first time
2010 Mar 11
1
Append to outfile in R CMD BATCH mode
Is there a way to append to the outfile when using R CMD BATCH? My code, right now, is: R CMD BATCH --slave --vanilla '--args place .2 -.1 .9 .6' StratificationSimulation example.output Everything else is working the way I'd like it. The first few lines of code of my script file are: options(echo=FALSE) cmd_args = commandArgs() print (cmd_args) #d <-
2011 Apr 20
1
What to do with positive likelihoods
Hi all, I'll preface this with saying I've gone through the archives, and am still in need of some help. I've been using this likelihood model with mean = 0 and s.d. = sqrt( (c + ( 1 / N1 ) + ( 1 / N2 ) ) * x * ( 1 - x )), where c is a genetic drift parameter (usually very small, like between .005 - .001), N1 and N2 are my population sizes (~200), and x is a value between 0 and 1.
2004 Mar 03
1
partial autocorrelation for Rt vs. Nt-1, ......., Nt-h
Dear list, following a previous querry we are still stuck! As pointed out by Erin Hodges the "ts" library includes a PACF function which reports the partial correlation of population density at time t against lagged population density. However, what we are trying to calculate is the partial correlation between rate of population change, Rt=log Nt/Nt-1, against lagged population
2010 Mar 11
1
Searching for option explanations
Hey all, Sorry if this is redundant, but I can't figure out a good search query for either the mailing list, or google, to find an answer to this. Let's say I have a couple of R options I'm interested in learning more about, but their details aren't explained in the command's help file. For example, for R CMD BATCH --help, it discusses the use of --restore, --save and
2004 Sep 06
1
qchisq (PR#7212)
Full_Name: David Clayton Version: 1.8.1 OS: Linux Submission from: (NULL) (131.111.126.242) qchisq behaves very strangely when ncp is passed as zero (forcing internal qnchisq to be called) when first argument is small. Eg > qchisq(1-1e-6, 1, ncp=0, lower.tail=TRUE) qchisq(1-1e-6, 1, ncp=0, lower.tail=TRUE) [1] 1024 while, if ncp is unspecified, > qchisq(1-1e-6, 1) qchisq(1-1e-6, 1)
2004 Jan 19
2
small bug on qchisq (PR#6442)
Full_Name: Drouilhet R?my Version: 1.8.1 OS: Linux Submission from: (NULL) (195.221.43.136) qchisq(1,10) works well but qchisq(1,10,ncp=0) does not work whereas ncp=0 is the default value of the function qchisq(1,10). (of course, 10 will be replaced by any integer value). Let us notice that this bug occurs only when applying probability one. (qchisq(seq(0,.9,.1),10,ncp=0) works very well).
2009 Oct 11
2
Accuracy (PR#13999)
Full_Name: Viktor Witkovsky Version: 2.9.2 OS: Windows XP Submission from: (NULL) (78.98.89.227) Hello, I have found strange behavior of the function qchisq (the non-central qchisq is based on inversion of pchisq, which is further based on pgamma). The function gives wrong results without any warning. For example: qchisq(1e-12,1,8.94^2,lower.tail=FALSE) gives 255.1840972465858 (notice that
2005 Aug 26
3
Matrix oriented computing
Hi, I want to compute the quantiles of Chi^2 distributions with different degrees of freedom like x<-cbind(0.005, 0.010, 0.025, 0.05, 0.1, 0.5, 0.9, 0.95, 0.975, 0.99, 0.995) df<-rbind(1:100) m<-qchisq(x,df) and hoped to get back a length(df) times length(x) matrix with the quantiles. Since this does not work, I use x<-c(0.005, 0.010, 0.025, 0.05, 0.1, 0.5, 0.9, 0.95, 0.975,
2010 Nov 12
1
what's wrong with this 'length' in function?
Hi all, I am having a trouble with this function I wrote ################################################### p26=function(x,alpha){ # dummy variable j=1 ci=matrix(ncol=2,nrow=3) while (j<4){ if (j==2) {x=x+c(-1,1)*0.5} ci[j,]= x+qnorm(1-alpha/2)^2/2+ c(-1,1)*qnorm(1-alpha/2)* sqrt(x+qnorm(1-alpha/2)^2/4) j=j+1 if (j==3) { # exact x=x-c(-1,1)*0.5
2003 Apr 13
2
Peculiarity in non-central qchisq for ncp > 294.92 ...
Hello all, Here's my query: Running R 1.6.2 on FreeBSD 5.0, and on WinXP, and I find that the following hangs the process: dchisq(alpha=0.01, df=1, ncp=295) but it does work for ncp < 294.92. Is this general? Best wishes to all, Andrew Andrew Robinson Ph: 208 885 7115 Department of Forest Resources Fa: 208 885 6226 University of Idaho E : andrewr at uidaho.edu PO
2007 Oct 10
5
chi2
Hello, I want to use the quantile function so I read the doc but I don't understand with this > qchisq(seq(0.05,0.95,by=0.05),df=(length(don)-1)) [1] 62667.11 62795.62 62882.42 62951.47 63010.74 63064.00 63113.39 63160.27 63205.65 63250.33 63295.04 63340.48 63387.48 63437.03 63490.53 63550.14 63619.68 [18] 63707.24 63837.16 Can you help me please?
2008 Nov 07
4
chi square table
Hi, How do we get the value of a chi square as we usually look up on the table on our text book? i.e. Chi-square(0.01, df=8), the text book table gives 20.090 > dchisq(0.01, df=8) [1] 1.036471e-08 > pchisq(0.01, df=8) [1] 2.593772e-11 > qchisq(0.01, df=8) [1] 1.646497 > nono of them give me 20.090 Thanks, cruz
2001 Mar 10
1
Bug in qchisq?
Hello developers and users: My system fails (the computer freezes) when I use the ncp parameter, with the lower.tail=FALSE option in the qchisq function. qchisq(0.025,31,ncp=1,lower.tail=FALSE) Thank you very much for your help. Kenneth Cabrera Universidad Nacional de Colombia ICNE Sede Medellin krcabrer at perseus.unalmed.edu.co PS I am using: $platform "i386-pc-mingw32"
2001 Mar 10
0
Re: [R] Bug in qchisq? (PR#875)
Kenneth Cabrera <krcabrer@epm.net.co> writes: > Hello developers and users: > > My system fails (the computer freezes) when I use the ncp parameter, > with the lower.tail=FALSE option in the qchisq function. > > qchisq(0.025,31,ncp=1,lower.tail=FALSE) Yup, that's a bug. We have in pnchisq.c 48 for (ux = 1.0; pnchisq(ux, n, lambda, lower_tail, log_p) <
2001 Mar 13
0
Re: [R] Bug in qchisq? (PR#875)
>>>>> "PD" == p dalgaard <p.dalgaard@biostat.ku.dk> writes: PD> Kenneth Cabrera <krcabrer@epm.net.co> writes: >> Hello developers and users: >> >> My system fails (the computer freezes) when I use the ncp parameter, >> with the lower.tail=FALSE option in the qchisq function. >> >>
2008 Jan 07
2
chi-squared with zero df (PR#10551)
Full_Name: Jerry W. Lewis Version: 2.6.1 OS: Windows XP Professional Submission from: (NULL) (24.147.191.250) pchisq(0,0,ncp=lambda) returns 0 instead of exp(-lambda/2) pchisq(x,0,ncp=lambda) returns NaN instead of exp(-lambda/2)*(1 + SUM_{r=0}^infty ((lambda/2)^r / r!) pchisq(x, df + 2r)) qchisq(.7,0,ncp=1) returns 1.712252 instead of 0.701297103 qchisq(exp(-1/2),0,ncp=1) returns 1.238938
2005 Jan 21
2
chi-Squared distribution
Dear Rs: outer(1:3, 1:3, function(df1, df2) qf(0.95, df1, df2)) I compare this F distribution results with the table, the answers were perfect. But I need to see for chi-sqaured distribution. When I employed the similar formula outer(1:3, 1:3, function(df1, df2) qchisq(0.95, df1, df2)) , I am getting unexpected results. I need to see the following values: p=0.750 ..... 1 1.323
2007 Jun 14
0
Confidence interval for coefficient of variation
This is a function I coded a few years ago to calculate a confidence interval for a coefficient of variation. The code is based on a paper by Mark Vangel in The American Statistician. I have not used the function much, but it could be useful for comparing cv's from different groups. Kevin Wright confint.cv <- function(x,alpha=.05, method="modmckay"){ # Calculate the
2005 Jan 21
2
chi-Squared distribution in Friedman test
Dear R helpers: Thanks for the previous reply. I am using Friedman racing test. According the the book "Pratical Nonprametric Statistic" by WJ Conover, after computing the statistics, he suggested to use chi-squared or F distribution to accept or reject null hypothesis. After looking into the source code, I found that R uses chi-sqaured distribution as below: PVAL <-