parcomputeW: Obtain quantities associated with W

In mapn/DAbayes: Bayesian Statistical Model for Climate-Change Detection and Attribution

Description

This function computes quantities in likelihood function based on ensembles y and model outputs x. This function is used in parallel computing of MCMC algorithm.

Usage

parcomputeW(y, x)

Arguments

y	an n by N matrix of ensemble members of measured variable (e.g., temperature increase)
x	a list of m elements under m forcing scenarios, each of which is model-output variable (e.g., temperature increase) under a specific forcing scenario

Value

a list of 6 elements

Author(s)

Pulong Ma <[e-mail]>

See Also

computeW

Examples

#################### simulate data ########################
set.seed(1234)
n <- 30 # number of spatial grid cells on the globe
N <- 10 # number of ensemble members
m <- 3 # number of forcing scenarios
Lj <- c(5, 3, 7) # number of runs for each scenario
L0 <- 8 # number of control runs without any external forcing scenario
trend <- 30
DAdata <- simDAdata(n, N, m, Lj, L0, trend)
# ensembles of the measured variable
y <- DAdata[[1]]
# model outputs for the measured variable under different forcing scenarios
x <- DAdata[[2]]
# model outputs for the measured variable without any external forcing scenario
x0 <- DAdata[[3]]
#################### end of simulation ####################

# center the data
y <- y - mean(y)
for(j in 1:m){
  x[[j]] <- x[[j]]-mean(x[[j]])
}

# precomputation for W
## Not run: 
outW <- parcomputeW(y,x)

## End(Not run)

mapn/DAbayes documentation built on May 21, 2019, 11:26 a.m.