model.parallel.run: Distribute model runs over multiple cores
In wdelva/MABC: Approximate Bayesian Computation with MICE
Description
Usage
Arguments
Value
Description
Allows faster execution of each wave of simulations
Usage
1
2
model.parallel.run(model, actual.input.matrix, seed_count = 0,
n_cores = 1)
Arguments
model
Wrapper function for the model
actual.input.matrix
Matrix with parameter combinations to be run
seed_count
Origin of random number seed
n_cores
Number of cores available for parallel running of the model
Value
a matrix of model features and the seed of the random number
generator
wdelva/MABC documentation built on May 27, 2019, 9:56 a.m.
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Description Usage Arguments Value
Description
Allows faster execution of each wave of simulations
Usage
1 2 | model.parallel.run(model, actual.input.matrix, seed_count = 0,
n_cores = 1)
|
Arguments
model |
Wrapper function for the model |
actual.input.matrix |
Matrix with parameter combinations to be run |
seed_count |
Origin of random number seed |
n_cores |
Number of cores available for parallel running of the model |
Value
a matrix of model features and the seed of the random number generator
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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