Package index • bifrost

All functions

as.data.frame(<bifrost_search_tuning_grid>): Convert a fixed-IC search tuning grid to a data frame
as.data.frame(<bifrost_search_tuning_selection>): Convert a tuned search-parameter selection to a data frame
as.data.frame(<bifrost_shift_recovery_evaluation>): Convert a shift-recovery evaluation to a data frame
as.data.frame(<bifrost_simulation_study>): Convert a bifrost simulation study to a data frame
as.data.frame(<regime_correlation_pca>): Convert Regime Correlation PCA Results to Data Frames
as.data.frame(<regime_integration_relationships>): Convert Regime Integration Relationship Results to Data Frames
as.data.frame(<regime_module_diagnostics>): Convert Regime Module Diagnostics to Data Frames
bifrost_example_file(): Locate a verified empirical example-data artifact
bootstrap_rate_distribution(): Bootstrap A Fitted Rate Distribution
compare_shift_magnitudes(): Compare Rate-Shift Magnitudes
createSimulationTemplate(): Create an Empirically Calibrated Simulation Template for bifrost
as.data.frame(<shift_magnitude_comparison>) as.data.frame(<shift_magnitude_comparison_set>) as.data.frame(<shift_magnitude_counts>) as.data.frame(<shift_magnitude_count_set>) as.data.frame(<rate_distribution_fit>) as.data.frame(<waiting_time_distribution_fit>): Coerce Shift And Distribution Summaries To Data Frames
evaluateShiftRecovery(): Evaluate Shift Recovery Against Simulated Ground Truth
fisher_z_transform(): Fisher's Z Transformation
fit_rate_distribution(): Fit Candidate Distributions To Rates
fit_regime_covariance_runs(): Fit Post-hoc Regime Covariance Models Across Runs
fit_regime_covariances(): Fit Independent Post-hoc Regime Covariance Models
fit_waiting_time_distribution(): Fit Candidate Distributions To Shift Waiting Times
generateViridisColorScale(): Generate Viridis Color Palette for Ranked Parameters
icTrajectory(): Create an Information-Criterion Trajectory
lineage_rates(): Compute Weighted Lineage Rates
plot(<icTrajectory>): Plot an Information-Criterion Trajectory
plot(<rateMap>): Plot rateMap Objects
plot(<rate_distribution_fit>): Plot A Fitted Rate Distribution
plot(<regime_correlation_pca>): Plot Regime Correlation PCA Results
plot(<regime_integration_relationships>): Plot Regime Rate-Integration Relationships
plot(<regime_module_diagnostics>): Plot Regime Module Diagnostics
plot(<shift_magnitude_comparison>): Plot One Shift-Magnitude Comparison
plot(<shift_magnitude_comparison_set>): Plot A Shift-Magnitude Comparison Set
plot(<shift_magnitude_count_set>): Plot A Shift-Magnitude Count Set
plot(<shift_magnitude_counts>): Plot One Shift Count Or Frequency Comparison
print(<bifrost_search>): Print method for bifrost search results
print(<bifrost_search_tuning_grid>): Print method for fixed-IC search tuning grids
print(<bifrost_search_tuning_selection>): Print method for tuned search-parameter selections
print(<bifrost_shift_recovery_evaluation>): Print method for shift-recovery evaluations
print(<bifrost_simulation_study>): Print method for bifrost simulation studies
print(<bifrost_simulation_template>): Print method for bifrost simulation templates
print(<rateMap>): Print a rateMap Object
rateMap(): Compute Branchwise Rate Maps Across Runs
rateMapControl(): Control Advanced rateMap() Options
rateMapRateFlags(): Control Near-Zero and Tail Rate Diagnostics for rateMap()
rateMapView(): Create a Display View of a rateMap Object
regime_correlation_pca(): Run PCA on Regime Correlation Structures
regime_integration_pgls(): Fit the Manuscript-style Regime Integration pGLS
regime_integration_relationships(): Analyze Rate-Integration Relationships Across Regimes
regime_module_diagnostics(): Diagnose PCA Axes with User-defined Trait Modules
runFalsePositiveSimulationStudy(): Run a False-Positive Simulation Study
runSearchTuningGrid(): Run a Fixed-IC Search Tuning Grid
runShiftRecoverySimulationStudy(): Run a Shift-Recovery Simulation Study
searchOptimalConfiguration(): Search for an Optimal Multi-Regime (Shift) Configuration on a Phylogeny
selectTunedSearchParameters(): Select Tuned Search Parameters from a Fixed-IC Grid
shift_magnitude_counts(): Count Inferred Rate Increases And Decreases
shift_magnitude_groups(): Define Shift-Magnitude Analysis Groups
shift_node_marks() plot(<shift_node_marks>) as.data.frame(<shift_node_marks>): Prepare And Plot Shift Node Marks On A Tree
shift_transitions(): Extract Regime Shift Transitions
shift_waiting_times(): Compute Waiting Times Between Regime Shifts
simulateNullDataset(): Simulate an Empirically Calibrated Null Replicate
simulateShiftedDataset(): Simulate an Empirically Calibrated Shifted Replicate
summarize_regime_covariance_runs(): Summarize Post-hoc Regime Covariance Models Across Runs
summarize_regime_covariances(): Summarize Post-hoc Regime Covariance Matrices