MultiBD (version 0.2.0)

bbd_prob: Transition probabilities of a birth/birth-death process

Description

Computes the transition pobabilities of a birth/birth-death process using the continued fraction representation of its Laplace transform

Usage

bbd_prob(t, a0, b0, lambda1, lambda2, mu2, gamma, A, B, nblocks = 256, tol = 1e-12, computeMode = 0, nThreads = 4, maxdepth = 400)

Arguments

t

time

a0

total number of type 1 particles at t = 0

b0

total number of type 2 particles at t = 0

lambda1

birth rate of type 1 particles (a two variables function)

lambda2

birth rate of type 2 particles (a two variables function)

mu2

death rate function of type 2 particles (a two variables function)

gamma

transition rate from type 2 particles to type 1 particles (a two variables function)

A

upper bound for the total number of type 1 particles

B

upper bound for the total number of type 2 particles

nblocks

number of blocks

tol

tolerance

computeMode

computation mode

nThreads

number of threads

maxdepth

maximum number of iterations for Lentz algorithm

Value

a matrix of the transition probabilities

References

Ho LST et al. 2015. "Birth(death)/birth-death processes and their computable transition probabilities with statistical applications". In review.

Examples

## Not run: 
# data(Eyam)
# 
# # (R, I) in the SIR model forms a birth/birth-death process
# 
# loglik_sir <- function(param, data) {
#   alpha <- exp(param[1]) # Rates must be non-negative
#   beta  <- exp(param[2])
#   N <- data$S[1] + data$I[1] + data$R[1]
#   
#   # Set-up SIR model with (R, I)
#   
#   brates1 <- function(a, b) { 0 }
#   brates2 <- function(a, b) { beta  * max(N - a - b, 0)  * b }
#   drates2 <- function(a, b) { 0 }
#   trans21 <- function(a, b) { alpha * b }
#   
#   sum(sapply(1:(nrow(data) - 1), # Sum across all time steps k
#              function(k) {
#                log(
#                  bbd_prob( # Compute the transition probability matrix
#                    t  = data$time[k + 1] - data$time[k], # Time increment
#                    a0 = data$R[k], b0 = data$I[k],       # From: R(t_k), I(t_k)
#                    brates1, brates2, drates2, trans21,
#                    A = data$R[k + 1], B = data$R[k + 1] + data$I[k] - data$R[k],
#                    computeMode = 4, nblocks = 80         # Compute using 4 threads
#                  )[data$R[k + 1] - data$R[k] + 1, 
#                    data$I[k + 1] + 1]                    # To: R(t_(k+1)), I(t_(k+1))
#                )
#              }))
# }
# 
# loglik_sir(log(c(3.204, 0.019)), Eyam) # Evaluate at mode
# ## End(Not run)