Find sampling algorithm and optimizers
Returns information on the sampling or estimation algorithm as well as optimization functions, or for Bayesian model information on chains, iterations and warmup-samples.
find_algorithm(x, ...)
x |
A fitted model. |
... |
Currently not used. |
A list with elements depending on the model.
For frequentist models:
algorithm, for instance "OLS" or "ML"
optimizer, name of optimizing function, only applies to specific models (like gam)
For frequentist mixed models:
algorithm, for instance "REML" or "ML"
optimizer, name of optimizing function
For Bayesian models:
algorithm, the algorithm
chains, number of chains
iterations, number of iterations per chain
warmup, number of warmups per chain
if (require("lme4")) {
data(sleepstudy)
m <- lmer(Reaction ~ Days + (1 | Subject), data = sleepstudy)
find_algorithm(m)
}
## Not run:
library(rstanarm)
m <- stan_lmer(Reaction ~ Days + (1 | Subject), data = sleepstudy)
find_algorithm(m)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.