Package: citydistR 0.1.0
Elif Kozan
citydistR: City-Adaptive Distance Modelling Utilities
Tools for distribution-aware and city-adaptive analysis of learning-based road-network distance estimates. Provides detour-factor diagnostics, a Topological Predictability Index, upper-tail summaries, modular robust losses, hybrid objective components, adaptive validation weights, and multi-criteria model evaluation. The functions are designed as reusable building blocks rather than a fixed model specification.
Authors:
citydistR_0.1.0.tar.gz
citydistR_0.1.0.zip(r-4.7-any)citydistR_0.1.0.zip(r-4.6-any)
citydistR_0.1.0.tar.gz(r-4.7-any)citydistR_0.1.0.tar.gz(r-4.6-any)
citydistR_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
citydistR/json (API)
| # Install 'citydistR' in R: |
| install.packages('citydistR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:22c77f73e4. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 119 | ||
| source / vignettes | OK | 152 | ||
| linux-release | OK | 99 | ||
| windows-devel | OK | 57 | ||
| windows-release | OK | 56 | ||
| wasm-release | OK | 66 |
Exports:adaptive_validation_scoreadaptive_weightscity_indicescombine_objectivescompare_distance_modelsdetour_factorevaluate_distance_modelhybrid_objectivemedian_df_regularizationpoint_lossrobust_loss_activetail95tpi
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| City-Adaptive Validation Score | adaptive_validation_score |
| City-Adaptive Validation Weights | adaptive_weights |
| City-Level Detour Diagnostics | city_indices |
| Combine Objective Components | combine_objectives |
| Compare Distance-Prediction Models | compare_distance_models |
| Compute Detour Factors | detour_factor |
| Evaluate Distance Predictions | evaluate_distance_model |
| Modular Hybrid Objective | hybrid_objective |
| Median-Based Detour Regularization | median_df_regularization |
| Pointwise Loss Aggregator | point_loss |
| Robust-Loss Activation Rule | robust_loss_active |
| Tail95 Detour-Heaviness Index | tail95 |
| Topological Predictability Index | tpi |