The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

dataSDA 0.2.5

New datasets (9 added, 114 total)

Nine interval time series (ITS) datasets from global financial markets and meteorology:

Interval time series (9)

• sp500.its — S&P 500 index daily OHLC intervals.
• djia.its — Dow Jones Industrial Average daily OHLC intervals.
• ibovespa.its — Ibovespa (Brazil) daily OHLC intervals.
• crude_oil_wti.its — WTI crude oil daily OHLC intervals.
• merval.its — MERVAL (Argentina) daily OHLC intervals.
• petrobras.its — Petrobras stock daily OHLC intervals.
• euro_usd.its — EUR/USD exchange rate daily OHLC intervals.
• shanghai_stock.its — Shanghai Composite daily OHLC intervals.
• irish_wind.its — Irish wind energy daily intervals.

Dataset renaming

Renamed 7 datasets with proper type suffixes for consistency:

Also added mushroom.int.mm (interval multi-modal format of mushroom data).

New functions (8 exported)

• Data conversion: aggregate_to_symbolic() — convert traditional data to symbolic data format.
• I/O: read_symbolic_csv(), write_symbolic_csv() — read/write symbolic data as CSV.
• Search: search_data() — search available datasets by keyword or type.
• Format conversion: to_all_interval_formats() — convert intervals to all supported formats at once.
• ARRAY format converters: ARRAY_to_MM(), ARRAY_to_RSDA(), ARRAY_to_iGAP(), MM_to_ARRAY(), RSDA_to_ARRAY(), SODAS_to_ARRAY(), iGAP_to_ARRAY().

Bug fixes

• Fixed int_dist p parameter bug.
• Fixed documentation for 19 datasets with incorrect column metadata.
• Fixed function documentation: @usage defaults, @details, and examples.

Other changes

• Updated vignette with new examples and content.
• Pre-built vignette to avoid CRAN timeout (eval gated by NOT_CRAN).
• Updated all dataset documentation with @section Metadata blocks.
• R CMD check --as-cran: 0 errors, 0 warnings, 0 notes.

dataSDA 0.2.2

New datasets (17 added, 105 total)

Seventeen new datasets from R packages (intkrige, RSDA, MAINT.Data, GPCSIV, HistDAWass, symbolicDA), the Billard & Diday (2007) textbook, and the QualAr Portuguese air quality network:

Interval-valued (12)

• utsnow.int — 415 Utah weather stations with snow load prediction intervals plus coordinates/elevation (from intkrige).
• lynne1.int — 10 observations with pulse rate, systolic, and diastolic pressure intervals (from RSDA).
• loans_by_risk_quantile.int — 35 Lending Club loan groups (A1-G5) with 4 quantile-based financial intervals (from MAINT.Data).
• judge1.int — 6 regions rated by Judge 1 on 4 interval variables (from GPCSIV).
• judge2.int — 6 regions rated by Judge 2 on 4 interval variables (from GPCSIV).
• judge3.int — 6 regions rated by Judge 3 on 4 interval variables (from GPCSIV).
• video1.int — 10 user groups with 5 video engagement interval metrics (from GPCSIV).
• video2.int — 10 user groups with 5 video engagement interval metrics (from GPCSIV).
• video3.int — 10 user groups with 5 video engagement interval metrics (from GPCSIV).
• lisbon_air_quality.int — 1096 daily observations of 8 pollutant concentration intervals from Lisbon (QualAr).

Histogram-valued (4)

• blood.hist — 14 gender-age groups with cholesterol, hemoglobin, and hematocrit histograms (from HistDAWass).
• china_climate_month.hist — 60 Chinese weather stations with 168 monthly climate histograms (from HistDAWass).
• china_climate_season.hist — 60 Chinese stations with 56 seasonal climate histograms (from HistDAWass).
• exchange_rate_returns.hist — 108 monthly exchange rate return histograms (from HistDAWass).

Mixed symbolic (1)

• polish_cars.mix — 30 Polish car models with 9 interval + 3 multinomial variables (from symbolicDA).

From Billard & Diday (2007) textbook (2)

• hierarchy.hist — 10 observations with hierarchical categories, conditional histograms, and cholesterol interval (Table 6.20).
• bird_color_taxonomy.hist — 20 birds with density/size histograms, tone, and fuzzy shade taxonomy (Tables 6.9/6.14).

dataSDA 0.2.1

New datasets (19 added, 88 total)

Nineteen new datasets from Billard & Diday (2020) Clustering Methodology for Symbolic Data, the HistDAWass R package, and other R packages:

Interval-valued (5)

• genome_abundances.int — 14 genome classes with 10 dinucleotide abundance intervals (Table 3-16).
• china_temp_monthly.int — 15 Chinese weather stations with 12 monthly temperature intervals + elevation (Table 7-9).
• ecoli_routes.int — 9 E. coli transport routes with 5 biochemical interval variables (Table 8-10).
• loans_by_risk.int — 35 Lending Club loan groups by risk level (A-G) with 4 financial intervals (from MAINT.Data).
• polish_voivodships.int — 18 Polish voivodships with 9 socio-economic interval variables (from clusterSim).

Histogram-valued (9)

• iris_species.hist — 3 iris species with 4 morphological histogram variables (Table 4-10).
• flights_detail.hist — 16 airlines with 5 flight performance histograms (Table 5-1).
• cover_types.hist — 7 forest cover types with 4 topographic histograms (Table 7-21).
• glucose.hist — 4 regions with blood glucose histograms (Table 4-14).
• state_income.hist — 6 US states with 4 income distribution histograms (Table 7-18).
• simulated.hist — 5 simulated observations with 2 histogram variables (Table 7-26).
• age_pyramids.hist — 229 countries with 3 age pyramid histograms (from HistDAWass).
• ozone.hist — 84 daily observations with 4 weather histograms (from HistDAWass).
• french_agriculture.hist — 22 French regions with 4 agricultural histograms (from HistDAWass).

Distribution-valued (1)

• household_characteristics.distr — 12 counties with 3 categorical distribution variables (Table 6-1).

Mixed symbolic (4)

• county_income_gender.hist — 12 counties with gendered income histograms + sample sizes (Table 6-16).
• joggers.mix — 10 jogger groups with pulse rate intervals + running time histograms (Table 2-5).
• census.mix — 10 census regions with 6 mixed-type variables: histograms, distributions, multi-valued sets, and intervals (Table 7-23).
• mtcars.mix — 5 car groups with 7 interval + 4 modal variables (from ggESDA).

dataSDA 0.2.0

New datasets (13 added, 69 total)

Thirteen new datasets extracted from R packages and the Billard & Diday (2006) textbook:

From R packages

• cardiological.int — 44 patients with 5 interval-valued physiological measurements (from RSDA).
• prostate.int — 97 prostate cancer patients with 9 clinical interval variables (from RSDA).
• uscrime.int — 46 US states with 102 interval-valued crime statistics (from RSDA).
• hardwood.hist — 5 hardwood tree species with 4 histogram-valued climate variables (from RSDA).
• synthetic_clusters.int — 125 observations in 5 clusters with 6 interval variables (from symbolicDA).
• environment.mix — 14 EPA state groups with mixed interval/modal environmental data (from ggESDA).

From Billard & Diday (2006) textbook tables

• weight_age.hist — 7 age groups with histogram-valued weight distributions (Table 3.10).
• hospital.hist — 15 hospitals with histogram-valued cost distributions (Table 3.12).
• cholesterol.hist — 14 gender-age groups with cholesterol histograms (Table 4.5).
• hemoglobin.hist — 14 gender-age groups with hemoglobin histograms (Table 4.6).
• hematocrit.hist — 14 gender-age groups with hematocrit histograms (Table 4.14).
• hematocrit_hemoglobin.hist — 10 observations with bivariate 2-bin histograms (Table 6.8).
• energy_usage.distr — 10 towns with categorical fuel/heating distributions (Table 3.7).

dataSDA 0.1.9

New datasets (7 added, 55 total)

Seven new interval-valued benchmark datasets from recent SDA papers (2020-2025):

• freshwater_fish.int — 12 freshwater fish species with 13 heavy metal bioaccumulation variables, 4 feeding classes (Andrade et al., 2025).
• fungi.int — 55 fungi specimens with 5 morphological variables, 3 genera: Amanita, Agaricus, Boletus (Andrade et al., 2025).
• iris.int — 30 interval observations of Fisher’s iris data, 4 sepal/petal variables, 3 species (Andrade et al., 2025).
• water_flow.int — 316 water flow sensor readings with 47 interval features, 2 classes (Andrade et al., 2025).
• wine.int — 33 wine samples with 9 chemical/physical property variables, 2 classes (Andrade et al., 2025).
• car_models.int — 33 Italian car models with 8 specification variables, 4 categories (Andrade et al., 2025).
• hdi_gender.int — 183 countries with 2 World Bank gender indicator intervals and ordinal HDI classification (Alcacer et al., 2023).

dataSDA 0.1.8

Vignette

• Comprehensive rewrite covering all 51 exported functions (was 18), organized into 14 sections: format detection/conversion, core stats, geometry, position, robust, shape, similarity, uncertainty, distance, histogram stats, and utilities.
• Fixed garbled characters, stale dataset references, and broken histogram example code.

dataSDA 0.1.7

New functions (2 exported)

• MM_to_RSDA() — convert MM format (_min/_max columns) to RSDA format (symbolic_tbl with complex-encoded intervals).
• iGAP_to_RSDA() — convert iGAP format to RSDA format via iGAP_to_MM → MM_to_RSDA.

Updated functions

• int_list_conversions() now returns 8 conversions (was 6), including MM_to_RSDA and iGAP_to_RSDA.
• int_convert_format() now supports to = "RSDA" for MM and iGAP sources with auto-detection.

Vignette

• Comprehensive rewrite covering all 51 exported functions (was 18), organized into 14 sections: format detection/conversion, core stats, geometry, position, robust, shape, similarity, uncertainty, distance, histogram stats, and utilities.
• Fixed garbled characters, stale dataset references, and broken histogram example code.

Tests

• 49 new tests for the new conversion functions and updated conversion registry (517 total, all passing).

dataSDA 0.1.6

Dataset naming convention

Adopted snake_case naming with type suffixes (.int, .hist, .mix, .distr, .iGAP) for all datasets. Renamed 10 existing datasets:

New datasets (16 added, 48 total)

• acid_rain.int, bats.int, credit_card.int, employment.int, oils.int, teams.int, tennis.int, temperature_city.int, trivial_intervals.int, world_cup.int (interval-valued)
• bird_species.mix, bird_species_extended.mix, town_services.mix (mixed symbolic)
• lung_cancer.hist (histogram-valued)
• energy_consumption.distr (distribution-valued)
• bank_rates, mushroom_fuzzy (other)

New functions (3 exported)

• Format detection and conversion (interval_format_conversions.R):
  • int_detect_format() — automatically detect interval data format (RSDA, MM, iGAP, SODAS).
  • int_list_conversions() — list available format conversion functions, with optional filtering by source/target format.
  • int_convert_format() — unified interface for all interval format conversions with auto-detection.

Other changes

• Updated vignette, examples, and tests to use new dataset names.
• 70 new tests for format detection and conversion helpers (468 total, all passing).
• R CMD check: 0 errors, 0 warnings, 0 notes.

dataSDA 0.1.5

New functions (31 exported)

• Interval distances (interval_dist.R): int_dist(), int_dist_matrix(), int_pairwise_dist(), int_dist_all() — 14 distance measures (GD, IY, L1, L2, CB, HD, EHD, nEHD, snEHD, TD, WD, minkowski, ichino, de_carvalho) with method aliases (euclidean, hausdorff, manhattan, city_block, wasserstein).
• Interval geometry (interval_geometry.R): int_width(), int_radius(), int_center(), int_overlap(), int_containment(), int_midrange().
• Position and scale (interval_position.R): int_median(), int_quantile(), int_range(), int_iqr(), int_mad(), int_mode() — all support 8 methods (CM, VM, QM, SE, FV, EJD, GQ, SPT).
• Robust statistics (interval_robust.R): int_trimmed_mean(), int_winsorized_mean(), int_trimmed_var(), int_winsorized_var().
• Distribution shape (interval_shape.R): int_skewness(), int_kurtosis(), int_symmetry(), int_tailedness().
• Similarity measures (interval_similarity.R): int_jaccard(), int_dice(), int_cosine(), int_overlap_coefficient(), int_tanimoto(), int_similarity_matrix().
• Uncertainty and variability (interval_uncertainty.R): int_entropy(), int_cv(), int_dispersion(), int_imprecision(), int_granularity(), int_uniformity(), int_information_content().

Refactoring

• Merged 6 interval conversion files into a single R/interval_format_conversions.R, organized by target format.
• Extracted shared internal helpers, reducing ~454 lines of duplicated code.
• R/interval_utils.R: consolidated 7 internal interval helpers, format-preparation functions (RSDA_format, set_variable_format, clean_colnames), and their internal helpers.
• R/histogram_utils.R: 8 internal helpers for histogram statistics.
• Renamed utils_validation.R to validation.R.
• R CMD check: 0 errors, 0 warnings, 0 notes. All 399 tests pass.

dataSDA 0.1.4

• Input validation for all 18 exported functions: every function now validates its inputs at entry, producing clear error messages instead of cryptic R internals errors.
• New R/utils_validation.R: 11 internal validation helpers centralizing all checks.
• RSDA_format fix: replaced 4 return("Error") with proper stop() calls.
• 62 new regression tests for input validation (399 total, all passing).
• R CMD check: 0 errors, 0 warnings.
• Added NEWS.md with changelog for all versions.

dataSDA 0.1.3

• Added testthat framework with 337 tests covering all 18 exported functions.
• 0 failures, 0 warnings, 0 skips.

dataSDA 0.1.2

• 18 exported functions for symbolic data format conversion and statistics.
• 32 datasets (interval-valued and histogram-valued) for symbolic data analysis.
• Support for MM, iGAP, RSDA, and SODAS data formats.
• Interval statistics: int_mean, int_var, int_cov, int_cor (8 methods).
• Histogram statistics: hist_mean, hist_var, hist_cov, hist_cor.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.