mle |
An array of dimension T \times (M + 2)\times N_{sample} containing MLE point estimates from the ensemble_fit object, where T is the total time, M is the number of simulators and N_{sample} is the number of samples. For each time step, the t th element of the array is a matrix where each column is a sample and the rows are the variables:
\left( y^{(t)}, \eta^{(t)}, z_1^{(t)}, z_2^{(t)}, \ldots, z_M^{(t)}\right)'
where y^{(t)} is the ensemble model's prediction of the latent truth value at time t ,
\eta^{(t)} is the shared short-term discrepancy at time t ,
z_i^{(t)} is the individual short-term discrepancy of simulator i at time t .
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samples |
An array of dimension T \times (M + 2)\times N_{sample} containing samples from the ensemble_fit object, where T is the total time, M is the number of simulators and N_{sample} is the number of samples. For each time step, the t th element of the array is a matrix where each column is a sample and the rows are the variables:
\left( y^{(t)}, \eta^{(t)}, z_1^{(t)}, z_2^{(t)}, \ldots, z_M^{(t)}\right)'
where y^{(t)} is the ensemble model's prediction of the latent truth value at time t ,
\eta^{(t)} is the shared short-term discrepancy at time t ,
z_i^{(t)} is the individual short-term discrepancy of simulator i at time t .
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