MCMC_sampling: learn W from data

In ZahraNSL/ODENEM:

Description

learn W from data

Usage

MCMC_sampling(
  dat,
  Q,
  r_0,
  rho,
  hyper.W,
  prior.theta,
  data.para,
  depletion.factor,
  depletion.factor.wt,
  method.wt,
  stimulation.value,
  stimulation.value.wt,
  seed = seed,
  ts,
  itr
)

Arguments

dat	feeded data of correspondings experiments,dimension nObs.nExp.times
Q	matrix of perturbation vectors Experiments*hidden nodes
r_0	start states of hidden nodes
rho	prior over edge existance
hyper.W	list of rho, lambda, nu, tau = hyperparameters of prior over W
prior.theta	prior probabilities over attachements E-nodes to S-nodes
depletion.factor	diag of W
depletion.factor.wt	diag of W in WT
method.wt	method for WildType state calculation: steadyState or timeSeries
stimulation.value	constant value for stimulation function
stimulation.value.wt	constant value for stimulation function in WildType case
seed	random seed
ts	Timesteps
itr	number of iterations for MCMC

Value

returns sampled Ws and LogLiklihoods

ZahraNSL/ODENEM documentation built on Dec. 31, 2020, 6:35 p.m.