r-statistics - Latest Comments

Re: Creating good looking survival curves – the ‘ggsurv’ function

Edwin Thoen — Tue, 13 Jan 2015 13:01:31 -0000

Thank you for your question KW87. Answer is unfortunately "no, it is not". Since more people did ask for it I will accommodate for it in upcoming version of ggsurv. Whenever GGally updates. Remind me if you don't see this option appear in a while.

Cheers,
Edwin

Re: Creating good looking survival curves – the ‘ggsurv’ function

Edwin Thoen — Tue, 13 Jan 2015 12:49:05 -0000

It's not perfect, but with a little bit of hacking in the survival object you come a long way. Maybe I'll integrate into upcoming versions. Good luck! Edwin

library(GGally)

library(magrittr)

survival.inverse <- function(sf.object){

sf.return <- sf.object

sf.return$surv <- 1 - sf.return$surv

sf.return$upper <- 1 - sf.return$upper

sf.return$lower <- 1 - sf.return$lower

sf.return

}

scrape.off.zero <- function(ggsurv.plot){

ggsurv.plot +

xlim(.00001, ggsurv.plot$data$time %>% max %>% add(1))

}

sf.lung <- survival::survfit(Surv(time, status) ~ 1, data = lung)

sf.lung.inv <- survival.inverse(sf.lung)

plot1 <- ggsurv(sf.lung.inv)

plot1 %>% scrape.off.zero

sf.sex <- survival::survfit(Surv(time, status) ~ sex, data = lung)

sf.sex.inv <- survival.inverse(sf.sex)

plot2 <- ggsurv(sf.sex.inv)

plot2 %>% scrape.off.zero

Re: How to load the {rJava} package after the error “JAVA_HOME cannot be determined from the Registry”

Shiv — Tue, 13 Jan 2015 11:50:53 -0000

Bingo! Thanks... worked.

Re: Creating good looking survival curves – the ‘ggsurv’ function

KW87 — Mon, 12 Jan 2015 18:21:46 -0000

Hi, this is really impressive work. Just wanna ask is it possible to adjust the "censored" dots to the same color as its own curve? That is, make the "male" dots green while the "female" dots keep red at the same time. Thanks.

Re: Updating R from R (on Windows) – using the {installr} package

Tal Galili — Mon, 05 Jan 2015 15:26:27 -0000

Thanks, my pleasure :)

Re: Updating R from R (on Windows) – using the {installr} package

DataElephant — Mon, 05 Jan 2015 11:17:38 -0000

I am R (windows) newbie. This package worked very well for me. Thank you!

Re: Edimax EW-7811Un USB wireless – connecting to a network (on ubuntu 11.10)

Tal Galili — Sat, 03 Jan 2015 14:20:02 -0000

Hi Ajardine,
I am happy to know this post (even though it was written over 3 years ago) is still helpful to people :)

Cheers,
Tal

Re: Edimax EW-7811Un USB wireless – connecting to a network (on ubuntu 11.10)

Ajardine — Fri, 02 Jan 2015 22:48:38 -0000

I resurrected an old PC with Xubuntu on the desktop and had exactly these same symptoms - dongle could see the wifi but couldn't connect. Downloaded Ubuntu on New Years day 2015, so apparently the newest version hasn't corrected the problem natively, I followed these instructions precisely and am connected! I've rebooted a few times, and things seem to be working perfectly. (had to use nano -w instead of gedit as default editor). Haven't been at a command prompt in years, but fixing things up took only an hour or two. Excellent, Excellent info here!

Re: Analyzing Your Data on the AWS Cloud (with R)

Wilian — Tue, 30 Dec 2014 07:54:56 -0000

Not in AWS, or not as far as I know. You could have excel in cloud here https://www.apponfly.com/en... but not sure if this is what you are looking for.

Re: “The next big thing”, R, and Statistics in the cloud

Natalia Garber, MBA — Mon, 29 Dec 2014 05:23:44 -0000

In hindsight, I can compare R with other products and in my opinion it did not hold up that well. Their marketplace is not that broad and extensive as Azure e.g. has. I miss a bunch of apps. For example, more cloud statistical sw could be included like NCSS http://www.ncss.com/ https://www.apponfly.com/en...

Re: Analyzing Your Data on the AWS Cloud (with R)

Tyler — Mon, 29 Dec 2014 04:58:48 -0000

Q: Can I run typical Microsoft apps such as Excel, Word and Powerpoint in AWS cloud?

Re: Creating good looking survival curves – the ‘ggsurv’ function

Nguyet M. Nguyen — Wed, 24 Dec 2014 01:16:59 -0000

Dear Edwin, I'm making an "inverse" survival curve using your code. I realized that in order to make such graph, I have to edit the y axis information in your ggplot comments from "y=surv" into "y=1-surv". So if I already installed GGally package, is there any support or suggestion on how to make inverse graph without the need of editing the code?
Thank you so much
Nguyet

Re: Creating good looking survival curves – the ‘ggsurv’ function

Nina — Wed, 03 Dec 2014 06:10:59 -0000

Hey
Thanks a lot! Is it also possible to inverse the plot?

Thanks in advance

Nina

Re: The dendextend package for visualizing and comparing trees of hierarchical clusterings (slides from useR!2014)

John — Tue, 02 Dec 2014 15:23:07 -0000

Great work, thanks for putting it out there!

Re: Do more with dates and times in R with lubridate 1.1.0

Bob — Wed, 26 Nov 2014 14:50:25 -0000

I did not go through all your post, but your last_day function may have a small bug unless this is what you want:
last_day(as.Date('2014-1-1')): "2013-12-31"
last_day(as.Date('2014-1-2')): "2014-01-31"
A working version might be something like:
last_day <- function(date) {
ceiling_date(date+days(1), "month") - days(1)
}

Re: Analyzing coverage of R unit tests in packages – the {testCoverage} package

Jack — Sun, 23 Nov 2014 04:48:27 -0000

This is good work. I also wrote function-level test coverage in a handful of extra lines presented in this pull request to testthat (in consideration by Hadley Wickham):
https://github.com/jackwase... (see R/test-package.r ) I figured at least testing each function would be 90% of the battle. For all the code paths, your package is great, other than masking 'library', 'require' and 'data', which is pretty scary, but maybe unavoidable in your approach.

'trace' is definitely the correct approach since it captures every step, not the sampling approach from 'profile'. Tracing every code path, however, hits performance very hard. Also, there is the danger of forcing the user into spending too much time into over-specifying tests for trivial functions: this could definitely be argued both ways, of course.

It is also implemented as an independent function in
https://github.com/jackwase...

Re: Analyzing coverage of R unit tests in packages – the {testCoverage} package

rapporter.net — Fri, 21 Nov 2014 14:40:53 -0000

Although this makes sense for sure, running the tests are out of the package's scope for some users, and `require` or `library` calls needed to run the testing packages can be found rather in the `.travis.yml` file that has nothing to do with "R CMD check" -- e.g. in my packages. This is on purpose, I do not run tests on "R CMD check" to save resources on CRAN. Anyway, this is a really minor issue, and your package rocks. Can you please look at this issue I opened recently: https://github.com/MangoThe... Thanks, Gergely

Re: Analyzing coverage of R unit tests in packages – the {testCoverage} package

Andy — Fri, 21 Nov 2014 13:40:07 -0000

I think it would be an interesting exercise to try to look through inst/tests for packages on CRAN to get an idea of the level of testing on the whole. I would be curious to see how many authors write tests outside of one of the frameworks mentioned in the article.

With regards to the DESCRIPTION file however whilst I agree that some authors may not list any testing package in the DESCRIPTION file I doubt that many get away without doing so when submitting to CRAN. Authors *should* be listing packages used for testing under the 'Suggests' field as this is one of the intended purposes of the field. The 'official' word on this in the 'Writing R Extensions' manual is that: "The ‘Suggests’ field uses the same syntax as ‘Depends’ and lists packages that are not necessarily needed. This includes packages used only in examples, tests or vignettes...". Additionally, if the test suite loads the testing package via 'require' or 'library' then it will need to be included in one of 'Depends', 'Imports' or 'Suggests' fields in order to pass an R CMD check, which is required for CRAN submission.

Re: Analyzing coverage of R unit tests in packages – the {testCoverage} package

Andy — Fri, 21 Nov 2014 13:17:29 -0000

What we are trying to achieve with testCoverage (or indeed what the concept of test coverage in general tries to achieve) is a measure of code quality via a simple metric. When deciding whether to use a package this metric should be taken into consideration along with a number of other factors such as those outlined in the article's introduction. As you suggest, a really comprehensive test suite would test the same piece of code multiple times with a variety of plausible input arguments but even then the code may still have bugs. So you 100% score on test coverage does not mean that the code works for all scenarios but it does indicate a degree of effort from the author.

Re: The ensurer package (validation inside pipes)

Francisco Rodriguez Algarra — Fri, 21 Nov 2014 02:52:41 -0000

Will definitely try it! Nice work!!

Re: The ensurer package (validation inside pipes)

josep2 — Wed, 19 Nov 2014 17:38:40 -0000

Great work!

Re: Updating R from R (on Windows) – using the {installr} package

Ravi — Tue, 18 Nov 2014 01:34:37 -0000

Very useful package! Thanks! All the best!

Re: Updating R from R (on Windows) – using the {installr} package

Jaroslaw Piskorski — Mon, 17 Nov 2014 17:50:02 -0000

Wow! I have to work in Windows now, and your package has made my life sooo much easier!

thank you very much
Jarek

Re: Creating good looking survival curves – the ‘ggsurv’ function

guest — Mon, 17 Nov 2014 11:47:47 -0000

Hi,

Could you show me an example how to plot more than 2 survival curves using your function please?

Thank you

Re: Exporting R output to MS-Word with R2wd (an example session)

Tal Galili — Fri, 07 Nov 2014 15:22:33 -0000

Thank you for the input Jim. I'll update the post.