Man pages for FastGaSP
Fast and Exact Computation of Gaussian Stochastic Process
| A_times_x_particle | Matrix-vector multiplication for particle systems |
| A_t_times_x_particle | Transpose matrix-vector multiplication for particle systems |
| Construct_G_exp | The coefficient matrix in the dynamic linear model when... |
| Construct_G_matern_3_2 | The coefficient matrix in the dynamic linear model when... |
| Construct_G_matern_5_2 | The coefficient matrix in the dynamic linear model when... |
| Construct_W0_exp | covariance of the stationary distribution of the state when... |
| Construct_W0_matern_3_2 | covariance of the stationary distribution of the state when... |
| Construct_W0_matern_5_2 | covariance of the stationary distribution of the state when... |
| Construct_W_exp | The conditional covariance matrix of the state in the dynamic... |
| Construct_W_matern_3_2 | The conditional covariance matrix for matern covariance with... |
| Construct_W_matern_5_2 | The conditional covariance matrix for matern covariance with... |
| extract_time_window | Extract time window from particle data |
| FastGaSP-package | Fast and Exact Computation of Gaussian Stochastic Process |
| fgasp | Setting up the Fast GaSP model |
| fgasp-class | Fast GaSP class |
| fit | Fit Particle Interaction Models |
| fit.fmou,fmou-method | The fast EM algorithm of multivariate Ornstein-Uhlenbeck... |
| fit.gppca,gppca-method | Parameter estimation for generalized probabilistic principal... |
| fit.particle.data | Fit method for particle data |
| fmou | Setting up the FMOU model |
| fmou-class | FMOU class |
| f_Vicsek_variation | Modified Vicsek Interaction Function |
| get_consecutive_data | Extract consecutive time steps data from particle... |
| Get_C_R_K_Q | matrices and vectors for the inverse covariance in the... |
| Get_L_inv_y | The multiplication of the inverse of L with y |
| Get_log_det_S2 | the natural logarithm of the determinant of the correlation... |
| Get_L_t_inv_y | The multiplication of the inverse of the transpose of L with... |
| Get_L_t_y | The multiplication of the transpose of L with y |
| Get_L_y | The multiplication of L with y |
| Get_Q_K | one-step-ahead predictive variance and Kalman gain |
| Get_R_y | The multiplication of R with y |
| gppca | Setting up the GPPCA model |
| gppca-class | GPPCA class |
| IKF | Inverse Kalman Filter - The multiplication of R with y with... |
| IKF_CG_particle | IKF-CG algorithm for one-interaction physical model with 1D... |
| IKF_CG_particle_cell | Inverse Kalman Filter with Conjugate Gradient for Particle... |
| Kalman_smoother | the predictive mean and predictive variance by Kalman... |
| log_lik | Natural logarithm of profile likelihood by the fast computing... |
| particle.data-class | Particle trajectory data class |
| particle.est-class | Particle interaction estimation class |
| predict.fgasp | Prediction and uncertainty quantification on the testing... |
| predict.fmou,fmou-method | Prediction and uncertainty quantification on the future... |
| predict.gppca,gppca-method | Prediction and uncertainty quantification on the future... |
| predictobj.fgasp-class | Predictive results for the Fast GaSP class |
| Sample_KF | Sample the prior process using a dynamic linear model |
| Sample_KF_post | Sample the posterior distribution of the process using the... |
| show.fgasp | Show an 'fgasp' object. |
| show.particle.data | Show method for particle data class |
| show.particle.est | Show method for particle estimation class |
| simulate_particle | Simulate particle trajectories |
| trajectory_data | Convert experimental particle tracking data to particle.data... |
| unnormalized_Vicsek | Unnormalized Vicsek model simulation |
