ea_mixG_DL_PT: Exact Algorithm for Langevin diffusion with pi as a tempered...

In rchan26/hierarchicalFusion: Divide-and-Conquer Monte Carlo Fusion

Exact Algorithm for Langevin diffusion with pi as a tempered mixture Gaussian

Description

Simulate Langevin diffusion using the Exact Algorithm with pi = exp(-(beta*x^4)/2)

Usage

ea_mixG_DL_PT(
  x0,
  y,
  s,
  t,
  n_comp,
  weights,
  means,
  sds,
  beta,
  precondition,
  bounds_multiplier = 1.1,
  logarithm
)

Arguments

x0	start value
y	end value
s	start time
t	end time
n_comp	integer number of components of mixture Gaussian
weights	vector: weights of mixture Gaussian
means	vector: means of mixture Gaussian
sds	vector: st.devs of mixture Gaussian
beta	real value
precondition	precondition value (i.e the covariance for the Langevin diffusion)
bounds_multiplier	scalar value to multiply bounds by (should greater than or equal to 1)
logarithm	logical value to determine if log probability is returned (TRUE) or not (FALSE)

Examples

weights <- c(0.4, 0.6)
means <- c(-8, 15)
sds <- c(1, 2)
beta <- 1/4
precondition <- 1.5
x0 <- -9
y <- -8
s <- 0
t <- 1
# simulate event probability of diffusion from -9 to -8 between [0,1]
ea_mixG_DL_PT(x0 = x0,
              y = y,
              s = s,
              t = t,
              n_comp = 2,
              weights = weights,
              means = means,
              sds = sds,
              beta = beta,
              precondition = precondition,
              bounds_multiplier = 1,
              logarithm = FALSE)
# simulate event probability of diffusion from -9 to 15 between [0,1]
x0 <- -9
y <- 15
ea_mixG_DL_PT(x0 = x0,
              y = y,
              s = s,
              t = t,
              n_comp = 2,
              weights = weights,
              means = means,
              sds = sds,
              beta = beta,
              precondition = precondition,
              bounds_multiplier = 1,
              logarithm = FALSE)

rchan26/hierarchicalFusion documentation built on Sept. 11, 2022, 10:30 p.m.