set_parameters {XDNUTS} | R Documentation |
Function that regulates the specifications of the xdnuts function.
set_parameters(
N_init1 = 50L,
N_adapt = 200L,
N_init2 = 75L,
burn_adapt_ratio = 0.1,
keep_warm_up = FALSE,
recycle_only_init = TRUE,
max_treedepth = 10L,
eps_jitter = 0.1,
L_jitter = 3L,
gamma = 0.05,
kappa = 0.75,
delta = NULL,
t0 = 10L,
M_type = "dense",
refresh = 0.1,
l_eps_init = NA_real_,
different_stepsize = FALSE,
mu = NA_real_,
M_cont = NULL,
M_disc = NULL
)
N_init1 |
an integer that regulates the number of samples used to adapt the step size. |
N_adapt |
an integer that regulates the number of samples used to estimate the Mass Matrix with fixed step size. |
N_init2 |
an integer that regulates the number of samples used to adapt the step size after the estimation of the Mass Matrix. |
burn_adapt_ratio |
a numeric scalar |
keep_warm_up |
a logical scalar that determines whether the warm-up samples should be returned. |
recycle_only_init |
a logical value which disables the recycling of the samples from each trajectory once the warm-up phase has terminated. |
max_treedepth |
an integer that regulates the maximum depth of the binary tree used to approximate Hamilton equation for the exploration of each energy level set of the phase space. |
eps_jitter |
a numeric scalar which regulates the amount of jittering used to perturb the value of the step size for each iteration of the chain after the warm-up phase. |
L_jitter |
an integer scalar that regulates the amount of jittering used to perturb the
value of the trajectory length if this is specified to be constant.
This occurs when the classic Hamiltonian Monte Carlo algorithm is used through the
|
gamma |
a numeric value that, in the Nesterov Dual Averaging algorithm, regulates the sensitivity of the step size updating scheme to fluctuations in the estimate of the mean Metropolis acceptance probability. |
kappa |
a numeric value that regulates the vanishing of Nesterov Dual Averaging algorithm for the estimation of the step size. |
delta |
a vector containing the Metropolis acceptance probabilities,
including both the global and those related to potential differences. Default values are (0.8,0.6).
If the second element of the vector is set to |
t0 |
an integer value that makes Nesterov Dual Averaging algorithm for the estimation of the step size less sensitive to early iterations. |
M_type |
a character value specifying the type of Mass Matrix to estimate:
|
refresh |
a numeric scalar bounded in |
l_eps_init |
a numeric scalar containing the logarithm of the initial value for the step size used to approximate Hamilton differential equation for phase space exploration. |
different_stepsize |
a boolean value indicating where the adaptation scheme should adapt different step size.
If |
mu |
a numeric scalar containing the value to which the step size is shrunken during the warm-up phase. |
M_cont |
a vector of length- |
M_disc |
a vector of length- |
an object of class control_xdnuts
containing a named list with all the above parameters.