braycir: Bayesian analysis of Rapid A-Ci response curves using Stan

In cdmuir/bayCi: Bayesian Photosynthetic Response Curves Using Stan

A-Ci

response curves using Stan

Description

Fit a single RACiR curve

Usage

braycir(data, empty, chains = 1, iter = 2000, warmup = floor(iter/2),
  thin = 1, cores = getOption("mc.cores", 1L), ...)

Arguments

data	An object of class racir containing data for all model variables.
empty	An object of class empty containing data from empty chamber to correct response data.
chains	Number of Markov chains (defaults to 1).
iter	Number of total iterations per chains (including warmup; defaults to 2000).
warmup	A positive integer specifying number of warmup (aka burnin) iterations. This also specifies the number of iterations used for stepsize adaptation, so warmup samples should not be used for inference. The number of warmup should not be larger than iter and the default is iter / 2.
thin	Thinning rate. Must be a positive integer. Set thin > 1 to save memory and computation time if iter is large.
cores	Number of cores to use when executing the chains in parallel (defaults to 1). Use detectCores to detect number of CPU cores on the current host.
...	Additional arguments passed to stan.

Value

An object of class racirfit

See Also

stan

Examples

library(bayCi)

cdmuir/bayCi documentation built on Jan. 19, 2020, 12:27 a.m.