Summary:
See title. A dense metric was used.
CSV header:
# stan_version_major = 2
# stan_version_minor = 26
# stan_version_patch = 1
# model = log_discourse_comp_model
# method = sample (Default)
# sample
# num_samples = 0
# num_warmup = 150
# save_warmup = 1
# thin = 1 (Default)
# adapt
# engaged = 1 (Default)
# gamma = 0.050000000000000003 (Default)
# delta = 0.80000000000000004 (Default)
# kappa = 0.75 (Default)
# t0 = 10 (Default)
# init_buffer = 50
# term_buffer = 0
# window = 100
# algorithm = hmc (Default)
# hmc
# engine = nuts (Default)
# nuts
# max_depth = 10 (Default)
# metric = dense_e
# metric_file = /tmp/tmp_4y6duce/6sl8gfq4.json
# stepsize = 1 (Default)
# stepsize_jitter = 0 (Default)
# id = 6
# data
# file = /tmp/tmp_4y6duce/32j_gv89.json
# init = /tmp/tmp_4y6duce/l2cfqou8.json
# random
# seed = 123456
# output
# file = /tmp/tmp_4y6duce/log_discourse_comp-202103181646-6-7quzdwmv.csv
# diagnostic_file = (Default)
# refresh = 100 (Default)
# sig_figs = -1 (Default)
# profile_file = profile.csv (Default)
# stanc_version = stanc3 ea3a31b
# stancflags =
CSV End
[...]
38.156,0.979962,0.381802,[...]
# Adaptation terminated
# Step size = 1
# Elements of inverse mass matrix:
Expected Output:
The step size should probably be different, something in the order of 0.381802.
See also this https://discourse.mc-stan.org/t/fitting-ode-models-best-efficient-practices/21018/80
Sorry for being terse.
Current Version:
v2.26.1
Summary:
See title. A dense metric was used.
CSV header:
CSV End
Expected Output:
The step size should probably be different, something in the order of
0.381802.See also this https://discourse.mc-stan.org/t/fitting-ode-models-best-efficient-practices/21018/80
Sorry for being terse.
Current Version:
v2.26.1