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RSDA  

R to Symbolic Data Analysis
View on CRAN: Click here


Download and install RSDA package within the R console
Install from CRAN:
install.packages("RSDA")

Install from Github:
library("remotes")
install_github("cran/RSDA")

Install by package version:
library("remotes")
install_version("RSDA", "3.2.5")



Attach the package and use:
library("RSDA")
Maintained by
Oldemar Rodriguez
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-05-29
Latest Update: 2025-06-02
Description:
Symbolic Data Analysis (SDA) was proposed by professor Edwin Diday in 1987, the main purpose of SDA is to substitute the set of rows (cases) in the data table for a concept (second order statistical unit). This package implements, to the symbolic case, certain techniques of automatic classification, as well as some linear models.
How to cite:
Oldemar Rodriguez (2013). RSDA: R to Symbolic Data Analysis. R package version 3.2.5, https://cran.r-project.org/web/packages/RSDA. Accessed 28 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:20), 1.0 (2013-05-29 17:33), 1.1 (2013-06-30 07:29), 1.2 (2014-03-18 18:20), 1.3 (2015-11-04 01:10), 1.4 (2017-05-30 23:04), 2.0.2 (2017-07-22 00:59), 2.0.3 (2018-02-14 22:08), 2.0.4 (2018-05-01 00:22), 2.0.5 (2018-07-31 01:10), 2.0.7 (2018-10-05 18:10), 2.0.8 (2018-10-11 01:00), 2.0 (2017-06-09 01:07), 3.0.1 (2020-01-21 08:50), 3.0.3 (2020-04-17 00:10), 3.0.4 (2020-06-07 19:40), 3.0.9 (2021-01-27 21:10), 3.0.12 (2022-07-04 22:40), 3.0.13 (2022-07-16 09:30), 3.0 (2019-10-22 07:30), 3.1.0 (2023-04-22 06:10), 3.2.1 (2023-11-10 15:53), 3.2.4 (2025-06-02 21:10)
Other packages that cited RSDA R package
View RSDA citation profile
Other R packages that RSDA depends, imports, suggests or enhances
Complete documentation for RSDA
Functions, R codes and Examples using the RSDA R package
Some associated functions: Cardiological . Maxima_and_Minima . R2.L . R2.U . RMSE.L . RMSE.U . RSDA . SDS.to.RSDA . SODAS.to.RSDA . Symbolic_mean . Symbolic_median . USCrime . VeterinaryData . abalone . as.data.frame.symbolic_histogram . as.data.frame.symbolic_interval . as.data.frame.symbolic_modal . as.data.frame.symbolic_set . calc.burt.sym . calc.k . calc.matrix.min . cardiologicalv2 . cash-.symbolic_histogram . cash-.symbolic_modal . cash-.symbolic_set . centers.interval.j . centers.interval . cfa.CVPRealz . cfa.Czz . cfa.MatrixZ . cfa.minmax.new . cfa.minmax . cfa.totals . check_quo_duplicated_names . classic.to.sym . cor . cov . data.frame.to.RSDA.inteval.table.j . data.frame.to.RSDA.inteval.table . deter.coefficient . dist.vect.matrix . dist.vect . dot-onAttach . ex1_db2so . ex_cfa1 . ex_cfa2 . ex_mcfa1 . ex_mcfa2 . example1 . example2 . example3 . example4 . example5 . example6 . example7 . extract_data . extract_meta . facedata . format.symbolic_histogram . format.symbolic_interval . format.symbolic_modal . format.symbolic_set . get_cats . get_props . int_prost_test . int_prost_train . interval.centers . interval.histogram.plot . interval.max . interval.min . interval.ranges . is.sym.histogram . is.sym.interval . is.sym.modal . is.sym.set . lynne1 . map_symbolic_tbl . mcfa.scatterplot . method_summary . neighbors.vertex . new.sym.histogram . new.sym.intreval . new.sym.modal . new.sym.set . newSobject . norm.vect . oils . optim.pca.distance.j . optim.pca.variance.j . pca.supplementary.vertex.fun.j . pca.supplementary.vertex.lambda.fun.j . pipe . plot.sym_tsne . plot.sym_umap . plot.symbolic_pca . plot.symbolic_tbl . plotX.slice . process.continue.variable . process.inter.cont.variable . process.mult.nominal.modif.variable . process.mult.nominal.variable . process.nominal.variable . read.sym.table . sd . sub-.sym.data.table . sub-.symbolic_tbl . sym.Interval.distance . sym.circle.plot . sym.continuos.plot . sym.dist.interval . sym.gbm . sym.glm . sym.hist.plot . sym.histogram . sym.interval . sym.interval.pc.limits . sym.interval.pc . sym.interval.pca.limits.new.j . sym.interval.plot . sym.interval.vertex.pca.j . sym.kmeans . sym.knn . sym.lm . sym.mcfa . sym.modal . sym.modal.plot . sym.nnet . sym.pca . sym.predict . sym.predict.symbolic_gbm_cm . sym.predict.symbolic_gbm_crm . sym.predict.symbolic_knn_cm . sym.predict.symbolic_knn_crm . sym.predict.symbolic_nnet_cm . sym.predict.symbolic_nnet_crm . sym.predict.symbolic_rf_cm . sym.predict.symbolic_rf_crm . sym.predict.symbolic_rt_cm . sym.predict.symbolic_rt_crm . sym.predict.symbolic_svm_cm . sym.predict.symbolic_svm_crm . sym.radar.data . sym.radar.plot . sym.rf . sym.rt . sym.scale.interval . sym.scatterplot . sym.set . sym.set.plot . sym.svm . sym.tsne . sym.umap . sym.var . to.v2 . to.v3 . uscrime_int . uscrime_intv2 . var.length . var . variance.princ.curve . vec_ptype_abbr.symbolic_histogram . vec_ptype_abbr.symbolic_interval . vec_ptype_abbr.symbolic_modal . vec_ptype_abbr.symbolic_set . vec_ptype_full.symbolic_histogram . vec_ptype_full.symbolic_interval . vec_ptype_full.symbolic_modal . vec_ptype_full.symbolic_set . vertex.interval.new.j . vertex.interval . vertex.pca.j . write.sym.table . 
Some associated R codes: RMSE.R . RSDA.R . centers_interval.R . centers_interval_j.R . data.R . data_frame_to_RSDA_inteval_table_j.R . deter_coefficient.R . dist_interval.R . dist_vect.R . dist_vect_matrix.R . interval_histogram_plot.R . mcfa_scatterplot.R . neighbors_vertex.R . norm_vect.R . optim_pca_distance_j.R . plot.symbolic_df.R . r2.R . read_sym_table.R . sds_to_rsda.R . sodas_to_rsda.R . sym.data.table_subset.R . sym.predict.R . sym_circle_plot.R . sym_glm.R . sym_interval_pc.R . sym_interval_pc_limits.R . sym_interval_pca.R . sym_interval_pca_limits_new_j.R . sym_interval_tsne.R . sym_interval_umap.R . sym_kmeans.R . sym_lm.R . sym_mcfa.R . sym_radar_plot.R . sym_regression.R . sym_scatterplot.R . sym_var.R . symbolic_df.R . symbolic_objects.R . utils-pipe.R . variance_princ_curve.R . vertex_interval.R . vertex_interval_new_j.R . vertex_pca_j.R . write_sym_table.R . zzz.R .  Full RSDA package functions and examples
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