Package: spinebil 1.0.5

Tina Rashid Jafari

spinebil: Investigating New Projection Pursuit Index Functions

Projection pursuit is used to find interesting low-dimensional projections of high-dimensional data by optimizing an index over all possible projections. The 'spinebil' package contains methods to evaluate the performance of projection pursuit index functions using tour methods. A paper describing the methods can be found at <doi:10.1007/s00180-020-00954-8>.

Authors:Ursula Laa [aut], Dianne Cook [aut], Tina Rashid Jafari [aut, cre]

spinebil_1.0.5.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
spinebil/json (API)

# Install 'spinebil' in R:
install.packages('spinebil', repos = c('https://uschilaa.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/uschilaa/spinebil/issues

On CRAN:

Conda:

quarto

5.32 score 10 scripts 206 downloads 30 exports 76 dependencies

Last updated from:570321f1c6. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE182
source / vignettesOK334
linux-releaseNOTE200
macos-releaseNOTE221
macos-oldrelNOTE199
windows-develNOTE128
windows-releaseNOTE135
windows-oldrelNOTE99
wasm-releaseOK140

Exports:basis_matrixbasis_vectorcmassRcompare_smoothingdata_gendistance_distdistance_to_spget_index_meanget_traceholesRjitter_anglejitter_pointsmine_indexmine_indexEnoise_genpipe_dataplot_rotationplot_smoothing_comparisonplot_traceppi_meanppi_noise_gridppi_noise_thresholdppi_samplesize_effectppi_scaleprofile_rotationscag_indexsin_dataspiral_datasquint_angle_estimatetime_sequence

Dependencies:abindalphahullashbitbit64bitopsbootcassowaryrclicliprcpp11crayondeldirdplyrenergyfarvergenericsgeozooggplot2gluegslgtablehmsigraphinterpisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvminervanlmepillarpkgconfigpolyclipprettyunitsprogresspurrrR.methodsS3R.ooR.utilsR6RColorBrewerRcppRcppArmadilloRcppEigenreadrrlangS7scalessgeostatspspatstat.dataspatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilssplancsstringistringrtensortibbletictoctidyrtidyselecttourrtzdbutf8vctrsviridisLitevroomwithr

More Descriptive Analysis of Projection Pursuit Indices
Overview | 1) Generating Synthetic Structures and Noise | Function usage | Example usage | Preview all structures | Polynomial features (type = "polynomial") | noise_gen(): noise distributions | Combining structure + noise | Return value | 2) Finding Projection Pursuit Index Mean | Example Usage | 3) Comparing Index Scale on Structured vs. Noisy Data | Function Usage | Boxplots: structured vs noise per variable pair | 4) Estimating a Noise Threshold for Projection Pursuit Indices | 5) Sample-Size Effects for Projection Pursuit Indices under Gaussian Noise | Plot the 95th-percentile
Rendered frommore_descriptives.qmdusingquarto::html

Last update: 2026-03-31
Started: 2025-08-30

Core Diagnostics for Projection Pursuit Indices
Overview | Data Generators | 1) compare_smoothing() | Function Usage | Inputs | Example Usage | Interpretation | Return value | 2) squint_angle_estimate() | Function usage | indexF (what kind of structure?) | cutoff (when do we call it visible?) | structure_plane (where is the best view?) | n and step_size | 3) get_trace() | 4) profile_rotation() | 5) time_sequence()
Rendered fromppi_diagnostics.qmdusingquarto::html

Last update: 2025-09-15
Started: 2025-08-30

An introduction to the spinebil package
About | Installation | Purpose | Example | Usage
Rendered fromspinebil.qmdusingquarto::html

Last update: 2025-08-30
Started: 2025-08-05

Readme and manuals

Help Manual

Help pageTopics
Generate 2-d basis in directions i, j in n dimensions (i,j <= n)basis_matrix
Generate basis vector in direction i in n dimensions (i <= n)basis_vector
Compare traces with different smoothing options.compare_smoothing
Generate Synthetic Data with Various Structuresdata_gen
Collecting all pairwise distances between input planes.distance_dist
Collecting distances between input planes and input special plane.distance_to_sp
Evaluate mean index value over n jittered views.get_index_mean
Tracing the index over an interpolated planned tour path.get_trace
Re-evaluate index after jittering the projection by an angle alpha.jitter_angle
Re-evaluate index after jittering all points by an amount alpha.jitter_points
Generate Synthetic Noisenoise_gen
Generating a sample of points on a pipepipe_data
Plot rotation traces of indexes obtained with profileRotation.plot_rotation
Plot the comparison of smoothing methods.plot_smoothing_comparison
Plot traces of indexes obtained with 'get_trace'.plot_trace
Simulate and Summarize Projection Pursuit Index (PPI) Valuesppi_mean
Estimate Noise Thresholds Across Sample Sizesppi_noise_grid
Estimate the 95th Percentile of a Projection Pursuit Index Under Noiseppi_noise_threshold
Simulate Effect of Sample Size on a Projection Pursuit Indexppi_samplesize_effect
Simulate and Compare Index Scale on Structured vs Noisy Datappi_scale
Test rotation invariance of index functions for selected 2-d data set.profile_rotation
Matching index functions to the required format.cmassR holesR mine_index mine_indexE scag_index
Generating sine wave samplesin_data
Generating spiral samplespiral_data
Estimating squint angle of 2-d structure in high-d dataset under selected index.squint_angle_estimate
Time each index evaluation for projections in the tour path.time_sequence