1. Univariate (1D) Visualizations | 1.1 Optimal 1D Histogram | 1.2 Fixed vs. Adaptive 1D Kernel Density (sskernel & ssvkernel) | 1.3 Comparing Window Functions (WinFunc) in Adaptive KDE | 2. Bivariate (2D) Visualizations | 2.1 Optimal 2D Histogram (sshist_2d) | 2.2 Fixed vs. Adaptive 2D Kernel Density (sskernel2d & ssvkernel2d)
Package: sshist 0.2.2
sshist: Optimal Density Estimation via Shimazaki-Shinomoto Method
Implements the Shimazaki-Shinomoto method for optimizing the bin width of histograms and the bandwidth of kernel density estimators. The framework minimizes the expected Mean Integrated Squared Error (MISE) and supports both 1D and 2D distributions, fixed and locally adaptive estimators, bootstrap confidence intervals, and 'OpenMP'-accelerated 'C++' 'backends'. Ideally suited for time-dependent rate estimation and identifying intrinsic data structures. For more details see Shimazaki and Shinomoto (2007) <doi:10.1162/neco.2007.19.6.1503> and Shimazaki and Shinomoto (2010) <doi:10.1007/s10827-009-0180-4>.
Authors:
sshist_0.2.2.tar.gz
sshist_0.2.2.zip(r-4.7)sshist_0.2.2.zip(r-4.6)sshist_0.2.2.zip(r-4.5)
sshist_0.2.2.tgz(r-4.6-x86_64)sshist_0.2.2.tgz(r-4.6-arm64)sshist_0.2.2.tgz(r-4.5-x86_64)sshist_0.2.2.tgz(r-4.5-arm64)
sshist_0.2.2.tar.gz(r-4.7-arm64)sshist_0.2.2.tar.gz(r-4.7-x86_64)sshist_0.2.2.tar.gz(r-4.6-arm64)sshist_0.2.2.tar.gz(r-4.6-x86_64)
sshist_0.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
sshist/json (API)
| # Install 'sshist' in R: |
| install.packages('sshist', repos = c('https://celebithil.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/celebithil/sshist/issues
Last updated from:74b2028895. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 181 | ||
| linux-devel-x86_64 | OK | 147 | ||
| source / vignettes | OK | 216 | ||
| linux-release-arm64 | OK | 175 | ||
| linux-release-x86_64 | OK | 144 | ||
| macos-release-arm64 | OK | 163 | ||
| macos-release-x86_64 | OK | 280 | ||
| macos-oldrel-arm64 | OK | 135 | ||
| macos-oldrel-x86_64 | OK | 287 | ||
| windows-devel | OK | 133 | ||
| windows-release | OK | 131 | ||
| windows-oldrel | OK | 131 | ||
| wasm-release | OK | 105 |
Exports:sshistsshist_2dsskernelsskernel2dssvkernelssvkernel2d
Dependencies:Rcpp
Advanced Density Visualization with ggplot2
Last update: 2026-07-09
Started: 2026-07-09
Introduction to sshist
1. Optimal 1D Histogram: sshist | Comparison with the standard approach | The S3 object | 2. Optimal 1D Kernel Density: sskernel & ssvkernel | Fixed Global Bandwidth (sskernel) | Locally Adaptive Bandwidth (ssvkernel) | Estimating Uncertainty with Bootstrap | 3. Optimal 2D Density Estimation | 2D Histogram: sshist_2d | 2D Kernel Density: sskernel2d and ssvkernel2d | References
Last update: 2026-07-09
Started: 2026-02-09
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Plot method for sshist objects | plot.sshist |
| Plot method for sshist_2d objects | plot.sshist_2d |
| Plot method for sskernel objects | plot.sskernel |
| Plot method for sskernel2d objects | plot.sskernel2d |
| Plot method for ssvkernel objects | plot.ssvkernel |
| Plot method for ssvkernel2d objects | plot.ssvkernel2d |
| Print method for sshist objects | print.sshist |
| Print method for sshist_2d objects | print.sshist_2d |
| Print method for sskernel objects | print.sskernel |
| Print method for sskernel2d objects | print.sskernel2d |
| Print method for ssvkernel objects | print.ssvkernel |
| Print method for ssvkernel2d objects | print.ssvkernel2d |
| Optimal Histogram Binning (Shimazaki-Shinomoto Method) | sshist |
| Optimal 2D Histogram Binning (Shimazaki-Shinomoto Method) | sshist_2d |
| Optimal 1D Kernel Density Estimation (Fixed Bandwidth) | sskernel |
| Optimal 2D Kernel Density Estimation (Fixed Bandwidth) | sskernel2d |
| Locally Adaptive 1D Kernel Density Estimation (Shimazaki-Shinomoto) | ssvkernel |
| Locally Adaptive 2D Kernel Density Estimation (Abramson's Method) | ssvkernel2d |
