Package: tempted 0.1.2
Pixu Shi
tempted: Temporal Tensor Decomposition, a Dimensionality Reduction Tool for Longitudinal Multivariate Data
TEMPoral TEnsor Decomposition (TEMPTED), is a dimension reduction method for multivariate longitudinal data with varying temporal sampling. It formats the data into a temporal tensor and decomposes it into a summation of low-dimensional components, each consisting of a subject loading vector, a feature loading vector, and a continuous temporal loading function. These loadings provide a low-dimensional representation of subjects or samples and can be used to identify features associated with clusters of subjects or samples. TEMPTED provides the flexibility of allowing subjects to have different temporal sampling, so time points do not need to be binned, and missing time points do not need to be imputed.
Authors:
tempted_0.1.2.tar.gz
tempted_0.1.2.zip(r-4.7-any)tempted_0.1.2.zip(r-4.6-any)tempted_0.1.2.zip(r-4.5-any)
tempted_0.1.2.tgz(r-4.6-any)tempted_0.1.2.tgz(r-4.5-any)
tempted_0.1.2.tar.gz(r-4.7-any)tempted_0.1.2.tar.gz(r-4.6-any)
tempted_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
tempted/json (API)
| # Install 'tempted' in R: |
| install.packages('tempted', repos = c('https://pixushi.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/pixushi/tempted/issues
- count_table - OTU read count table from the ECAM data
- meta_table - Meta data table from the ECAM data
- processed_table - Central-log-ratio (clr) transformed OTU table from the ECAM data
Last updated from:4062dca4db. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 161 | ||
| source / vignettes | OK | 186 | ||
| linux-release | OK | 158 | ||
| macos-release | OK | 225 | ||
| macos-oldrel | OK | 162 | ||
| windows-devel | OK | 118 | ||
| windows-release | OK | 104 | ||
| windows-oldrel | OK | 110 | ||
| wasm-release | OK | 117 |
Exports:aggregate_featureest_test_subjectformat_temptedplot_feature_summaryplot_metafeatureplot_time_loadingratio_featurereconstructsvd_centralizetdenoisetemptedtempted_all
Dependencies:bootclicpp11crscubaturefarverggplot2gluegtableisobandlabelinglatticelifecycleMASSMatrixMatrixModelsnpquadprogquantregR6RColorBrewerRcpprlangS7scalesSparseMsurvivalvctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Aggregate features using feature loadings | aggregate_feature |
| Caculate the Bernoulli kernel | bernoulli_kernel |
| OTU read count table from the ECAM data | count_table |
| Estimate subject loading of testing data | est_test_subject |
| Format data table into the input of tempted | format_tempted |
| Meta data table from the ECAM data | meta_table |
| Plot nonparametric smoothed mean and error bands of features versus time | plot_feature_summary |
| Plot nonparametric smoothed mesan and error bands of meta features versus time | plot_metafeature |
| Plot the temporal loading functions | plot_time_loading |
| Central-log-ratio (clr) transformed OTU table from the ECAM data | processed_table |
| Take log ratio of the abundance of top features over bottom features | ratio_feature |
| Reconstruct tensor from low dimensional components | reconstruct |
| Remove the mean structure of the temporal tensor | svd_centralize |
| Calculate the de-noised temporal tensor | tdenoise |
| Decomposition of temporal tensor | tempted |
| Run all major functions of tempted | tempted_all |