Package index • weathergenr

All functions

adjust_precipitation_qm(): Adjust Daily Precipitation with Gamma Quantile Mapping Under Monthly Scenario Factors
analyze_wavelet_additive(): Additive wavelet analysis with CWT diagnostics
analyze_wavelet_spectrum(): Continuous Wavelet Spectral Analysis with COI-Aware Significance
apply_climate_perturbations(): Apply Monthly Climate Perturbations to Gridded Daily Weather Series
build_historical_dates(): Build Historical Date Table
calculate_monthly_pet(): Calculate Monthly Potential Evapotranspiration (PET)
compute_area_averages(): Compute Area-Averaged Daily and Annual Climate Series
compute_water_year(): Calculate water year from a date vector
create_all_diagnostic_plots(): Create all diagnostic plots
diagnose_precip_qm(): Compute Diagnostics for Precipitation Quantile Mapping
estimate_monthly_markov_probs(): Estimate Monthly Occurrence-State Markov Transition Probabilities
evaluate_weather_generator(): Evaluate Stochastic Weather Generator Performance
filter_warm_pool(): Filter and sample WARM realizations using distributional, tail, and spectral criteria
find_leap_day_indices(): Find leap-day (Feb 29) indices in a date vector
generate_noleap_dates(): Generate a no-leap (365-day) daily date sequence
generate_symmetric_dummy_points(): Generate Dummy Points to Enforce Symmetric Facet Axes
generate_weather(): Generate Synthetic Gridded Daily Weather Series
get_result_index(): Safely Get or Sample an Index from a Vector
knn_sample(): K-Nearest Neighbor (KNN) Sampling from Candidates
markov_next_state(): Determine Next State in a First-Order Markov Chain
match_transition_positions(): Get Positions of a Specific Occurrence State Transition Within Candidate Indices
modwt_mra(): MODWT multiresolution analysis (MRA)
normalize_calendar(): Normalize Calendar to 365 Days
plot_wavelet_global_spectrum(): Plot Global Wavelet Spectrum
plot_wavelet_power(): Plot Wavelet Power and Global Wavelet Spectrum
prepare_evaluation_data(): Prepare Generator Output for Evaluation
print(<precip_qm_diagnostics>): Print method for precipitation QM diagnostics
print(<wavelet_additive>): Print method for additive wavelet analysis
read_netcdf(): Read NetCDF variables into tidy data frames
resample_weather_dates(): Resample Daily Weather Dates Using Annual KNN and Markov Chain Logic
run_weather_generator(): Run weathergenr end-to-end (generate and evaluate)
simulate_warm(): Simulate synthetic series with Wavelet Autoregressive Modeling (WARM)
summary(<precip_qm_diagnostics>): Summarize precipitation QM diagnostics
validate_quantile_mapping(): Validate precipitation quantile mapping adjustments
write_netcdf(): Write Gridded Data to a NetCDF File (Template-Based)