Introduction | Example 1: Binary Data | Data | Full Workflow Call | Load and Inspect Precomputed Results | Parallel Analysis | Bootstrap Stability Diagnostics | ALSI Computation | Category Projections | Example 2: Ordinal Data | Ordinal ALSI Computation | Example 3: Continuous Data | Continuous ALSI Computation and Domain Contributions | Comparison with SEPA Plane-Wise Summaries | Session Information
Package: SEPA 0.1.0
Se-Kang Kim
SEPA: Segment Profile Extraction via Pattern Analysis
Implements the Segment Profile Extraction via Pattern Analysis method for row-mean-centered multivariate data. Core capabilities include SVD-based row-isometric biplot construction, bias-corrected and accelerated, and percentile bootstrap confidence intervals for domain coordinates and per-person direction cosines, Procrustes alignment of bootstrap replicates across planes, parallel analysis for dimensionality selection, and segment profile reconstruction in planes defined by pairs of singular dimensions. A synthetic Woodcock-Johnson IV look-alike dataset is provided for examples and testing. The method is described in Kim and Grochowalski (2019) <doi:10.1007/s00357-018-9277-7>.
Authors:
SEPA_0.1.0.tar.gz
SEPA_0.1.0.tar.gz(r-4.7-any)SEPA_0.1.0.tar.gz(r-4.6-any)
SEPA_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SEPA/json (API)
| # Install 'SEPA' in R: |
| install.packages('SEPA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- fake_wj - Synthetic Woodcock-Johnson IV look-alike dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:f8bb3bf01b. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 162 | ||
| source / vignettes | OK | 180 | ||
| linux-release-x86_64 | OK | 117 | ||
| wasm-release | OK | 92 |
Exports:boot_cis_alldraw_sepa_biplotparallel_analysis_ipsatizedpercentile_ci_matrun_sepasepa_stats_allsimulate_sepa_fake_wjwrite_long_to_widewrite_matrix_wide
Dependencies:boot
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| BCa (with percentile fallback) confidence intervals for all bootstrap indices | boot_cis_all |
| Draw a SEPA row-isometric SVD biplot | draw_sepa_biplot |
| Synthetic Woodcock-Johnson IV look-alike dataset | fake_wj |
| Parallel analysis for ipsatized data | parallel_analysis_ipsatized |
| Percentile confidence intervals from a matrix of bootstrap draws | percentile_ci_mat |
| Print method for sepa_result objects | print.sepa_result |
| Run a complete SEPA analysis | run_sepa |
| Compute SEPA statistics: plane-fit rho and direction cosines | sepa_stats_all |
| Simulate a synthetic Woodcock-Johnson IV look-alike dataset | simulate_sepa_fake_wj |
| Reshape a long data frame to wide and write a CSV | write_long_to_wide |
| Write an n x p matrix as a wide CSV with an ID column | write_matrix_wide |