melt
Multiple empirical likelihood tests (by ropensci)
canaper
Categorical Anaysis of Neo- and Paleo-endemism in R (by ropensci)
| melt | canaper | |
|---|---|---|
| 1 | 1 | |
| 11 | 7 | |
| - | - | |
| 7.8 | 5.8 | |
| 23 days ago | 12 months ago | |
| R | R | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
melt
Posts with mentions or reviews of melt.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-30.
-
Peer-Reviewing Statistical R Packages
melt: Multiple Empirical Likelihood Tests by Eunseop Kim, reviewed by Alex Stringer and Pierre Chausse, edited by Paula Moraga
canaper
Posts with mentions or reviews of canaper.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-30.
-
Peer-Reviewing Statistical R Packages
canaper: Categorical Analysis of Neo- And Paleo-Endemism in R, by Joel H. Nitta, reviewed by Luis Osorio and Klaus Schliep, edited by Toby Dylan Hocking
What are some alternatives?
When comparing melt and canaper you can also consider the following projects:
aorsf - Accelerated Oblique Random Survival Forests
bruceR - 📦 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.