I am searching for a good R package to align multiple spectra.
Thanks.
I don't know exactly what you're looking for, but have you looked at http://bioconductor.org ? The PROcess package seems to have an align method. Also this site here has links to software and source code that may be relevant, even if not in R.
Related
I searched at various places but didn't find any relevant packages for this. I need to know how people proceed with FIEGARCH Modelling in any software.
you can use oxmetric or s_pluse software for this work.
I was wondering if anyone out there has found a nice package for R to analyse eye-tracking data?
I came across eyetrackR but as far as I can tell there is no English support documentation available:
http://read.psych.uni-potsdam.de/pmr2/index.php?option=com_content&view=article&id=43:eyetrackr&catid=13:r-playground&Itemid=15
I will move onto another freeware that handles eye-tracking data if I need to but was really hoping there would be something accessible in R.
Ideas?
Cheers.
It would help if you could explain which kind of analyses you are intending to do. There are many different approaches depending on the research question and the research field. Many approaches involve the detection of fixations and saccades as a first step. An R package that can be used for fixation detection is called saccades and is available on CRAN. See also the Github page of the package for examples and screenshots.
A new eye-tracking analysis package for R (eyetrackingR) was recently released. It provides a variety of methods that handle data preparation/cleaning, visualization, and analysis.
Here's a list of several dozen instances of researcher contributed code (FOSS) for post-acquisition summarization and analysis of eye-movement data. You may be able to find something to suit your needs there.
List is provided in case anyone stumbling across this thread may find it useful.
https://github.com/davebraze/FDBeye/wiki/Researcher-Contributed-Eye-Tracking-Tools
colorout is no longer on CRAN. As #user2647661 points out below, the package is still being maintained and can be downloaded from the author's website.
My question: Is there another R package that provides similar functionality or at least a quick hack that shows errors in red? (I use R inside a Gnome Terminal on Ubuntu.)
I am aware of Alex's question about printing errors in red. #Eric Fail's answer suggests that something like this can be build using error handling functions. However, I am not familiar enough with R to fully understand his suggestion. Has anybody implemented something like this yet?
The package is no longer on CRAN but it's still being maintained. Please, look at http://www.lepem.ufc.br/jaa/colorout.html
Does anybody know where I can download the R package "cart" that can help create Gastner's
"Mapping with Diffusion-based Cartograms" ? I tried a install.package on R and says it's not available
for R 2.15. There is a page on R-forge about it but it doesn't explain how to download the package.
Thanks.
Way late to the game, but from what I can tell there's not much happening for the cart package; my recent efforts with cartogramming in R have pushed me towards two alternatives: Rcartogram within R (available from the GitHub repository) and ScapeToad, a program written in JS.
Advantage of the former is that you don't have to leave R (better for long-term project management), however it's a bit arcane to use (requires converting your shapefile to a density grid & then figuring out how to use an interpolation method, etc.).
Advantage of the latter is that it's got a very simple point-and-click GUI--add shapefile, create cartogram wizard, export shapefile, voila.
Both are based on the Gastner-Newman diffusion-based algorithm.
If you check the build page you'll see that at the moment the package fails to build. I thought it might be something minor but I've put in a little bit of work so far and it's still failing to build on my machine.
You might want to email the authors and ask them. You could also try their forum but it looks like it hasn't seen much activity lately.
How do people learn about giving an R package a namespace? I find the documention in "R Extensions" fine, but I don't really get what is happening when a variable is imported or exported - I need a dummy's guide to these directives.
How do you decide what is exported? Is it just everything that really shouldn't required the pkg:::var syntax? What about imports?
Do imports make it easier to ensure that your use of other package functions doesn't get confused when function names overlap?
Are there special considerations for S4 classes?
Packages that I'm familiar with that use namespaces such as sp and rgdal are quite complicated - are there simple examples that could make things clearer?
I have a start on an answer on the devtools wiki: https://r-pkgs.org/Metadata.html
Few years later here....
I consolidated findings from Chambers, other StackOverflow posts, and lots of tinkering in R:
https://blog.thatbuthow.com/how-r-searches-and-finds-stuff/
This is less about implementing NAMESPACE/IMPORTS/DEPENDS and more about the purpose of these structures. Answers some of your questions.
The clearest explanation I've read is in John Chambers' Software for Data Analysis: Programming with R, page 103. I don't know of any free online explanations that are better than what you've already found in the R Extensions manual.
You could also pick an easy, small package and follow it.
I semi-randomly looked at digest which is one of my smaller packages. I loads a (small) dynamic library and exports one symbol, the digest() function. Here is the content of the NAMESPACE file:
## package has dynamic library
useDynLib(digest)
## and one and only one core function
export(digest)
Have a look at the rest of the source files and maybe try to read Writing R Extensions alongside looking at the example, and do some experiments.
http://www.stat.uiowa.edu/~luke/R/namespaces/morenames.pdf