smcDE: This function estimate parameters in DEs via SMC based on...

In shijiaw/smcDE: Adaptive semiparametric Bayesian differential equations via sequential Monte Carlo methods

Description

This function estimate parameters in DEs via SMC based on collocation

Usage

smcDE(
  data,
  times,
  seed,
  knots,
  CESSthresholds,
  NP,
  resampleThreshold,
  alambda,
  blambda,
  sigmac,
  DEmodel
)

Arguments

data	a list with each element being a trajectory with measurement error
times	a list with each element being the time we record data
seed	the random seeds for propagation and resampling in SMC
CESSthresholds	relative conditional effective sample size (0, 1) in SMC
NP	the number of particles in SMC
resampleThreshold	the threshold triggering resampling in SMC
alambda	hyper-parameter for tuning parameter lambda
blambda	hyper-parameter for tuning parameter lambda
sigmac	the standard deviation of the basis coefficients c
DEmodel	options for DE models: 1 (ODE), 2 (DDE1), 3 (DDE2) in manuscript
knots	the location we put knots

shijiaw/smcDE documentation built on Nov. 25, 2020, 2:14 p.m.