EnsembleSample: A constructor for the `EnsembleSample` object

Description

A constructor for the EnsembleSample class. These objects are generated automatically using the generate_sample function.

EnsembleSample(ensemble_fit, mle, samples)

An object of class EnsembleSample

ensemble_fit: An EnsembleFit object containing the fitted ensemble model.
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 tth 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 $t$.
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 tth 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 $t$.