Other packages > Find by keyword >

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", "3.2.1")



Attach the package and use:
library("RSDA")
Maintained by
Oldemar Rodriguez
[Scholar Profile | Author Map]
First Published: 2013-05-29
Latest Update: 2023-04-22
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 3.2.1, https://cran.r-project.org/web/packages/RSDA. Accessed 26 Mar. 2025.
Previous versions and publish date:
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)
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
Downloads during the last 30 days
02/2402/2502/2602/2702/2803/0103/0203/0303/0403/0503/0603/0703/0803/0903/1003/1103/1203/1303/1403/1503/1603/1703/1803/1903/2003/2103/2203/2303/2403/25Downloads for RSDA05101520253035404550TrendBars

Today's Hot Picks in Authors and Packages

sAIC  
Akaike Information Criterion for Sparse Estimation
Computes the Akaike information criterion for the generalized linear models (logistic regression, Po ...
Download / Learn more Package Citations See dependency  
photobiologyPlants  
Plant Photobiology Related Functions and Data
Provides functions for quantifying visible (VIS) and ultraviolet (UV) radiation in relation to the ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
fPortfolio  
Rmetrics - Portfolio Selection and Optimization
A collection of functions to optimize portfolios and to analyze them from different points of view. ...
Download / Learn more Package Citations See dependency  
DySS  
Dynamic Screening Systems
In practice, we will encounter problems where the longitudinal performance of processes needs to be ...
Download / Learn more Package Citations See dependency  
Maintainer: Lu You (view profile)
provenance  
Statistical Toolbox for Sedimentary Provenance Analysis
Bundles a number of established statistical methods to facilitate the visual interpretation of large ...
Download / Learn more Package Citations See dependency  

23,842

R Packages

207,311

Dependencies

64,420

Author Associations

23,781

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA