Man pages for ngme2
Linear Latent Non-Gaussian Models with Flexible Distributions
| adagrad | AdaGrad SGD optimization |
| adam | Adam SGD optimization |
| adamW | AdamW SGD optimization |
| adaptive_gd | Adaptive gradient descent |
| ar | ngme AR(p) model specification |
| ar1 | ngme AR(1) model specification |
| ARcov | Helper function to compute AR(p) autocovariance |
| argo_float | Argo float dataset |
| arma | ngme ARMA(p, q) model specification |
| arma11 | Convenience wrapper for ARMA(1,1) |
| batch_decay | Batch/checkpoint decay helper |
| batch_means_ci | Pooled Batch-Means Confidence Intervals from Multiple Chains |
| batch_means_estimator | Batch-Means Covariance Estimator for SGD Trajectories |
| bfgs | BFGS optimization |
| bv | Ngme bivariate model specification |
| bv_matern | Ngme bivariate model with Matern sub_models |
| calibrate_inv_exp_lambda_driven_nig | Calibrate Inverse-Exponential Prior for NIG Driven Noise |
| cienaga | The swamp of Cienaga Grande in Santa Marta, Colombia |
| cienaga.border | The x y location of the border of the swamp of Cienaga Grande... |
| compare_noise_kld | Compare noise objects using Kullback-Leibler divergence |
| compute_index_corr_from_map | Helper function to compute the index_corr vector |
| compute_log_like | Compute Gaussian log-likelihood |
| compute_ngme_ci | Refit an Existing ngme Object with SGD and Compute... |
| compute_ngme_sgld_samples | Refit an Existing ngme Object with SGLD and Extract Samples |
| compute_score_given_pred | Compute the scores given the prediction |
| control_ngme | Generate control specifications for the ngme model |
| control_opt | Generate control specifications for 'ngme()' function. |
| control_opt_batch_ci | Generate CI-focused control settings for batch-means... |
| create_paired_cv_splits | Create paired indices for bivariate cross-validation Ensures... |
| cross_validation | Compute the cross-validation for the ngme model Perform... |
| f | Specifying a latent process model (wrapper function for each... |
| gal | The Generalized Asymmetric Laplace (GAL) Distribution |
| generic | Generic precision matrix operator |
| generic_ns | Non-stationary precision matrix operator with custom matrix... |
| get_data_from_formula | Extracts design matrix from a formula and data. |
| get_noise_param | get the parameters of the noise |
| get_parameter_distance | Calculate parameter distance from true values |
| get_trace_trajectories | Get trace trajectories from ngme fitting |
| get_trajectories | get the trajectories of parameters of the model |
| gig | The Generalised Inverse-Gaussian (GIG) Distribution |
| ig | The Inverse-Gaussian (IG) Distribution |
| igam | The Inverse-Gamma (IGam) Distribution |
| iid | ngme iid model specification |
| make_time_series_cv_index | Create Time Series Cross-Validation Indices |
| matern | ngme Matern SPDE model specification |
| mean_list | taking mean over a list of nested lists |
| merge_noise | Merge 2 noise into 1 noise |
| merge_replicates | Merge model of replicates into model of 1 replicate given... |
| momentum | Momentum SGD optimization |
| name2fun | Convert transformation name to function |
| ngme | Fit an additive linear mixed effect model over replicates |
| ngme2 | Inference and prediction for mixed effects models with... |
| ngme_as_sparse | Convert sparse matrix into sparse dgCMatrix |
| ngme_batch_ci | Batch-Means Confidence Intervals from an ngme Fit |
| ngme_cov_matrix | variance of the data or the latent field |
| ngme_make_mesh_repls | ngme make mesh for different replicates |
| ngme_model_types | Show ngme model types |
| ngme_noise | ngme noise specification |
| ngme_noise_types | Show ngme noise types |
| ngme_optimizers | List supported optimizers |
| ngme_parse_formula | Parse the formula for ngme function |
| ngme_post_samples | posterior samples of different latent models |
| ngme_prior_types | Show ngme priors |
| ngme_result | Access the result of a ngme fitted model |
| ngme_sgld_ci | Quantile Confidence Intervals from SGLD Samples |
| ngme_sgld_samples | Extract Posterior-like Samples from Stored SGLD Trajectories |
| ngme_ts_make_A | Make observation matrix for time series |
| ngme_update | Check whether a newer stable version of ngme2 is available |
| nig | The Normal Inverse-Gaussian (NIG) Distribution |
| noise_moments | Moments of stationary NIG and GAL noise |
| openmp_test | Test OpenMP availability and report the number of threads. |
| ou | Ornstein-Uhlenbeck Process Model |
| plot.ngme_noise | Plot the density of one or more stationary noise objects |
| plot.parameter_distance | Plot method for parameter_distance |
| pm25_quarterly_2022 | Quarterly PM2.5 monitor averages over CONUS in 2022 |
| poly_decay | Polynomial schedule helper |
| posterior_plot | Plot Posterior Distributions from SGLD Samples |
| precision_matrix_multivariate | Compute the precision matrix for multivariate model |
| precision_matrix_multivariate_spde | Compute the precision matrix for multivariate spde Matern... |
| precond_sgd | Preconditioner SGD optimization |
| predict.ngme | Predict function of ngme2 predict using ngme after estimation |
| print.ngme | Print an ngme model |
| print.ngme_model | Print ngme model |
| print.ngme_noise | Print ngme noise |
| print.ngme_operator | Print ngme operator |
| print.ngme_replicate | Print ngme object |
| print.ngme_trajectories | Print method for ngme_trajectories |
| print.noise_kld_comparison | Print method for noise_kld_comparison |
| print.parameter_distance | Print method for parameter_distance |
| prior_half_cauchy | Prior Half-Cauchy |
| prior_inv_exponential | Prior Inverse-Exponential |
| prior_none | Prior None |
| prior_normal | Prior Normal |
| prior_pc_sd | Prior PC-SD |
| priors | Prior Container |
| re | ngme random effect model |
| rmsprop | Root Mean Square Propagation (RMSProp) SGD optimization |
| rw1 | Random Walk Model of Order 1 (RW1) |
| rw2 | Random Walk Model of Order 2 (RW2) |
| sgd | Vanilla SGD optimization |
| sgld | Stochastic Gradient Langevin Dynamics (SGLD) optimization |
| simulate.ngme | Simulate from a ngme object (possibly with replicates) |
| simulate.ngme_model | Simulate latent process with noise |
| simulate.ngme_noise | Simulate ngme noise object |
| spacetime | Ngme space-time non-separable model specification |
| stepsize_control | Unified stepsize control |
| stepsize_decay | Stepsize decay schedule |
| stepsize_schedule | Stepsize schedule |
| summary.ngme | Summary of ngme fit result |
| summary.ngme_batch_ci | Summary for Batch-Means CI Results |
| test_ngme | Test ngme function |
| tp | ngme tensor-product model specification |
| traceplot | Trace plot of ngme fitting |
| var1 | ngme VAR(1) bivariate model specification (Cayley... |
