Description Usage Arguments Value Author(s) See Also
This function updates parameters (gamma, beta, sigma, lambda) for the Bayesian statistical model. gamma is updated with a discrete uniform prior; beta is updated with the noninformative prior 1 and random-walk proposal; log of sigma (variance in W) is updated with the normal prior and random-walk proposal; lambda is updated with the normal prior and random-walk proposal.
1 | DA_theta_MH(outW, theta, prior_theta, ADtheta, n, N, Lj, tol = 1e-10)
|
outW |
a 7 by 1 list containing precomputed quantities associated with W from the output of function computeW(...) |
theta |
a list of 4 elements containing parameters in the MCMC algorithm |
prior_theta |
parameters in prior distributions |
ADtheta |
a 6 by 1 list containing quantities to adjust mean and covariance in proposal distributions |
n |
number of grid cells over the globe |
N |
number of ensemble members |
Lj |
an m by 1 vector containing the number of runs for each forcing scenario |
tol |
a very small value to avoid numerical instability |
a list of 4 elements containing updated parameters in the MCMC iteration
Pulong Ma <mpulong@gmail.com>
DA_GIBBS function
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