Man pages for bivarhr
Bivariate Hurdle Regression with Bayesian Model Averaging
| add_qsig | Add BH-adjusted q-values and significance stars |
| add_sheet | Add a worksheet to an Excel workbook with flexible content |
| bivarhr-package | bivarhr: Bivariate Hurdle Regression |
| build_design | Build Design Matrices for Bivariate Hurdle Model |
| contrafactual_ATE | Contrafactual Average Treatment Effects (ATE) for the... |
| disc_terciles | Discretize Numeric Vector into Terciles |
| dot-as_num1 | Coerce to numeric and return first element |
| dot-build_model_with_floor | Build CmdStan model with custom FLOOR constant |
| dot-first_pvalue | Extract a p-value from nested test objects |
| dot-get_coef | Safely extract coefficient matrix from an object |
| dot-get_pval | Extract p-value from RTransferEntropy result |
| dot-get_stat | Extract TE statistic from RTransferEntropy result |
| dot-is_binary_like | Check if Vector is Binary-like |
| dot-read_te_all | Read transfer entropy results from CSV files |
| dot-scalar1 | Coerce to numeric scalar safely |
| dot-scalar1_chr | Coerce to character scalar safely |
| dot-write_sheet | Safely write a data frame to an Excel worksheet |
| export_results | Export Analysis Results |
| export_results_xlsx | Export Results to an Excel Workbook |
| fit_one | Fit Single Bivariate Hurdle Model |
| get_hurdle_model | Get Default Hurdle Model |
| load_saved_results | Load Saved Results from Directory |
| make_lags | Create Lag Matrix |
| normalize_names | Normalize character names by stripping BOM and NBSP |
| placebo_temporal | Temporal Placebo Test via Time-Index Permutations |
| predict_multistep | Multi-step Predictive Simulation for the Bivariate Hurdle... |
| prewhiten_bin_glm | Pre-whiten binary series with logistic GLM |
| prewhiten_count_glm | Pre-whiten count series with GLM / NegBin model |
| prewhiten_rate_glm | Pre-whiten rate series with log-link Gaussian GLM |
| print.bivarhr_hmm | Print method for bivarhr_hmm objects |
| print_floor_smoketest | Print summary of FLOOR smoke test (ELPD ranking invariance) |
| rc_auto | Read CSV with automatic delimiter detection |
| read_bma_all | Read and consolidate BMA weight tables |
| rolling_oos | Rolling Out-of-Sample Forecast Evaluation |
| run_dbn | Fit a Two-Slice Dynamic Bayesian Network (DBN) for I, C, and... |
| run_eba | Extreme-Bounds Analysis (EBA) over Control-Variable... |
| run_hmm | Hidden Markov Model (HMM) for Path Dependence (Counts I and... |
| run_sensemakr | Sensitivity Analysis to Unobserved Confounding (sensemakr) |
| run_synth_bsts | Synthetic Control via BSTS (CausalImpact) |
| run_transfer_entropy | Transfer Entropy for Counts, Rates, and Binary Series |
| run_varx | Fit VARX model with diagnostics for I and C |
| select_by_bma | Select Best Model via Bayesian Model Averaging |
| smoketest_floor_elpd_invariance | Smoke Test for FLOOR ELPD Invariance |
| standardize_continuous | Standardize Continuous Columns |
| standardize_continuous_in_place | Standardize Continuous Columns In Place |
| summarise_hurdle_top3_posthoc | Summarise top-3 Hurdle-NB models across control combos |
| summarise_placebo_top3_posthoc | Summarise top-3 temporal placebo results |
| summarise_te_top3_by_type_posthoc | Summarise top-3 transfer entropy results by type |
| summarise_te_top3_posthoc | Summarise top-3 transfer entropy results (global) |
| summarise_tvarstar_posthoc | Summarise nonlinear time-series models (TVAR and LSTAR) |
| summarise_varx_posthoc | Summarise VARX model fit and diagnostics |
