similar to: asypow.noncent: how does it work?

Displaying 5 results from an estimated 5 matches similar to: "asypow.noncent: how does it work?"

2018 Apr 25
1
Can't Get Lattice Histogram Minor Tick Marks to Work
Thanks Jeff, I attached a file with the program to my earlier email because the posting guide seemed to imply that non-binary attachments would work. But I see that the file was stripped off. I installed the program file on a web site, but when I downloaded it, the line breaks were stripped out. So I've included the program below: ------------------------------------------------------- #
2018 Apr 25
0
Can't Get Lattice Histogram Minor Tick Marks to Work
Per the Posting Guide, why didn't you post the reproducible R code example? On April 24, 2018 8:22:15 PM PDT, Donald Macnaughton <donmac at matstat.com> wrote: >I'm drawing a paneled histogram using the lattice package. I've >succeeded in >adding minor tick marks to the vertical axis, but I can't get the >desired >number of minor tick marks between the major
2018 Apr 25
3
Can't Get Lattice Histogram Minor Tick Marks to Work
I'm drawing a paneled histogram using the lattice package. I've succeeded in adding minor tick marks to the vertical axis, but I can't get the desired number of minor tick marks between the major tick marks. I've attached a self-contained program to illustrate the problem. Thanks for your help, Don Macnaughton Here's my sessionInfo: R version 3.4.3 (2017-11-30) Platform:
2003 Aug 01
1
ncp t & Fortran error & power of some tests
Hi everybody, I have three questions to ask us: a) R incorporates a function for the Non-central T distribution which unfortunately and, as you know, is not available in Splus 4.5. In http://www.stats.ox.ac.uk/pub/Swin I found the Don MacQueen?s noncent.zip but when I run it in Splus 4.5 the following error message appears: "Error in .Fortran ("vectnc",: "VECTNC" is not a
2006 Mar 08
1
power and sample size for a GLM with Poisson response variable
Craig, Thanks for your follow-up note on using the asypow package. My problem was not only constructing the "constraints" vector but, for my particular situation (Poisson regression, two groups, sample sizes of (1081,3180), I get very different results using asypow package compared to my other (home grown) approaches. library(asypow) pois.mean<-c(0.0065,0.0003) info.pois <-