particle.est-class {FastGaSP} | R Documentation |
Particle interaction estimation class
Description
S4 class for storing estimated parameters and predictions for particle interaction models.
Objects from the Class
Objects of this class are created by the fit.particle.data
(via fit
) method when applied to particle.data
objects to estimate interaction parameters and make predictions.
Slots
data_type
:Object of class
character
. Specifies the type of data ("simulation" or "experiment").model
:Object of class
characterOrNULL
. Specifies the model type for simulation data (e.g., "Vicsek" or "two_interactions_Vicsek"). NULL for experimental data.D_y
:Object of class
numeric
. Dimension of the output space.num_interaction
:Object of class
numeric
. Number of interactions.parameters
:Object of class
numeric
. Vector of estimated parameters with length 2*D_y + 1:First D_y elements: beta (inverse range parameters)
Next D_y elements: tau (variance-noise ratios)
Last element: interaction radius
sigma_2_0_est
:Object of class
numeric
. Estimated noise variance.predictions
:object of class
listOrNULL
. Contains predicted means and 95% confidence intervals (lower and upper bounds) for the particle interactions if testing inputs are given.training_data
:Object of class
list
. Contains the training data used in the GP model, obtained using the estimated interaction radius.gp_weights
:Object of class
matrix
. Contains the weights from the GP computation (A^T_j Sigma_y^(-1) y) used for prediction, with each column corresponding to a type of interaction j.
Methods
- show:
Method for displaying summary information about the estimated parameters.
References
Fang, X., & Gu, M. (2024). The inverse Kalman filter. arXiv:2407.10089.
See Also
fit.particle.data
for more details about how to create a particle.est
object.
particle.data-class
for the input data structure