Description Usage Arguments Value
Computes the SDP solution under the case of growth noise, implementation errors in harvesting, and meaurement errors in the stock assessment.
1 2 3 | SDP_multiple_uncertainty(f, p, x_grid, h_grid, Tmax = 25,
sigmas = c(sigma_g = 0, sigma_m = 0, sigma_i = 0),
pdfn = pdfn, profit = function(x, h) pmin(x, h))
|
f |
the growth function of the escapement population (x-h) should be a function of f(t, y, p), with parameters p |
p |
the parameters of the growth function |
x_grid |
the discrete values allowed for the population size, x |
h_grid |
the discrete values of harvest levels to optimize over |
sigma |
is the shape parameters for noise distribution (sigma_g, sigma_m, sigma_i) (default is no noise) |
pdfn |
is the probability density function (same functional form is used for growth, measure, implement). (Default is uniform) |
profit |
is the profit function (defaults to the realized harvest) |
The D matrix giving the optimal harvest for each possible state in each timestep. Hence the optimal policy at time t is given by the policy function D[,t]. Values of D[,t] correspond to the index of h_grid. Indices of of D[,t] correspond to states in y_grid.
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