It is with great pleasure that I can announce that Ryacas version 1.1.0 has now been accepted into Journal of Open Source Software and same version released to CRAN. (The source code is available at https://github.com/mikldk/ryacas/.)
I already wrote about Ryacas many times before. I will refer you to the “Getting started” and “The high-level (symbol) interface” vignettes or one of the others available at the CRAN page or the package’s website.
It is with great pleasure that I can announce that Ryacas version 1.0.0 is now released to CRAN (https://cran.r-project.org/package=Ryacas). I wish to thank all co-authors: Rob Goedman, Gabor Grothendieck, Søren Højsgaard, Grzegorz Mazur, Ayal Pinkus.
It means that you can install the package by (possible after binaries have been built):
install.packages("Ryacas") Followed by:
library(Ryacas) (The source code is available at https://github.com/mikldk/ryacas/.)
Now you have the yacas computer algebra system fully available!
In a recent blog post I tried to get yacas to solve a system of polynomial equations. Unfortunately it could not do that, so I solved it numerically instead. Now it is possible – together with many other systems of polynomial equations thanks to fixing a small error in yacas. It has now been fixed, also in Ryacas (development version), so hurry up and update Ryacas to the latest version 0.
Update on Aug 9, 2022: In the code chunk below, sd = summary(fit_gam)$scale) was changed to sd = sqrt(summary(fit_gam)$scale)):
y_sim <- matrix(rnorm(n = prod(dim(exp_val_sim)), mean = exp_val_sim, sd = summary(fit_gam)$scale), nrow = nrow(exp_val_sim), ncol = ncol(exp_val_sim)) Thanks to David Kaplan (IRD, France)
Finding prediction intervals (for future observations) is something different than finding confidence intervals (for unknown population parameters).
Here, I demonstrate one approach to doing so.
Update Aug 27, 2019: I wrote a new blog post showing that Ryacas can now solve the system of equations directly without using optim().
As you may know, I am maintaining the Ryacas package (with online documentation) for doing symbolic mathematics (and other stuff) in R using the yacas software (with online documentation).
Søren Højsgaard and I have been preparing a new major release of Ryacas (see blog post on it).