Showing 9 of total 9 results (show query)
epiverse-trace
linelist:Tagging and Validating Epidemiological Data
Provides tools to help storing and handling case line list data. The 'linelist' class adds a tagging system to classical 'data.frame' objects to identify key epidemiological data such as dates of symptom onset, epidemiological case definition, age, gender or disease outcome. Once tagged, these variables can be seamlessly used in downstream analyses, making data pipelines more robust and reliable.
Maintained by Hugo Gruson. Last updated 5 days ago.
datadata-structuresepidemiologyepiverseoutbreakssdg-3structured-data
7 stars 8.69 score 61 scripts 2 dependents
oobianom
shinyStorePlus:Secure in-Browser and Database Storage for 'shiny' Inputs, Outputs, Views and User Likes
Store persistent and synchronized data from 'shiny' inputs within the browser. Refresh 'shiny' applications and preserve user-inputs over multiple sessions. A database-like storage format is implemented using 'Dexie.js' <https://dexie.org>, a minimal wrapper for 'IndexedDB'. Transfer browser link parameters to 'shiny' input or output values. Store app visitor views, likes and followers.
Maintained by Obinna Obianom. Last updated 1 months ago.
28 stars 8.29 score 93 scripts 1 dependents
vgherard
r2r:R-Object to R-Object Hash Maps
Implementation of hash tables (hash sets and hash maps) in R, featuring arbitrary R objects as keys, arbitrary hash and key-comparison functions, and customizable behaviour upon queries of missing keys.
Maintained by Valerio Gherardi. Last updated 5 months ago.
3 stars 7.36 score 82 scripts 28 dependents
rpahl
container:Extending Base 'R' Lists
Extends the functionality of base 'R' lists and provides specialized data structures 'deque', 'set', 'dict', and 'dict.table', the latter to extend the 'data.table' package.
Maintained by Roman Pahl. Last updated 3 months ago.
containerdata-structuresdequedictsets
16 stars 7.13 score 140 scripts
mingzehuang
latentcor:Fast Computation of Latent Correlations for Mixed Data
The first stand-alone R package for computation of latent correlation that takes into account all variable types (continuous/binary/ordinal/zero-inflated), comes with an optimized memory footprint, and is computationally efficient, essentially making latent correlation estimation almost as fast as rank-based correlation estimation. The estimation is based on latent copula Gaussian models. For continuous/binary types, see Fan, J., Liu, H., Ning, Y., and Zou, H. (2017). For ternary type, see Quan X., Booth J.G. and Wells M.T. (2018) <arXiv:1809.06255>. For truncated type or zero-inflated type, see Yoon G., Carroll R.J. and Gaynanova I. (2020) <doi:10.1093/biomet/asaa007>. For approximation method of computation, see Yoon G., Müller C.L. and Gaynanova I. (2021) <doi:10.1080/10618600.2021.1882468>. The latter method uses multi-linear interpolation originally implemented in the R package <https://cran.r-project.org/package=chebpol>.
Maintained by Mingze Huang. Last updated 3 years ago.
data-analysisdata-miningdata-processingdata-sciencedata-structuresmachine-learningmixed-typesstatistics
16 stars 6.65 score 46 scripts 1 dependents
rethomics
behavr:Canonical Data Structure for Behavioural Data
Implements an S3 class based on 'data.table' to store and process efficiently ethomics (high-throughput behavioural) data.
Maintained by Quentin Geissmann. Last updated 4 years ago.
biological-data-analysisdata-structuresethomics
6 stars 5.91 score 64 scripts 7 dependents
spkaluzny
splusTimeSeries:Time Series from 'S-PLUS'
A collection of classes and methods for working with indexed rectangular data. The index values can be calendar (timeSeries class) or numeric (signalSeries class). Methods are included for aggregation, alignment, merging, and summaries. The code was originally available in 'S-PLUS'.
Maintained by Stephen Kaluzny. Last updated 6 months ago.
3.95 score 20 scripts 1 dependents
yukai-yang
R6DS:R6 Reference Class Based Data Structures
Provides reference classes implementing some useful data structures. The package implements these data structures by using the reference class R6. Therefore, the classes of the data structures are also reference classes which means that their instances are passed by reference. The implemented data structures include stack, queue, double-ended queue, doubly linked list, set, dictionary and binary search tree. See for example <https://en.wikipedia.org/wiki/Data_structure> for more information about the data structures.
Maintained by Yukai Yang. Last updated 2 years ago.
binary-search-treesdata-structuresdequedictionarydoubly-linked-listfunctional-programmingmapqueuereference-classstacktraversal
5 stars 3.40 score 5 scripts
annennenne
PCADSC:Tools for Principal Component Analysis-Based Data Structure Comparisons
A suite of non-parametric, visual tools for assessing differences in data structures for two datasets that contain different observations of the same variables. These tools are all based on Principal Component Analysis (PCA) and thus effectively address differences in the structures of the covariance matrices of the two datasets. The PCADSC tools consist of easy-to-use, intuitive plots that each focus on different aspects of the PCA decompositions. The cumulative eigenvalue (CE) plot describes differences in the variance components (eigenvalues) of the deconstructed covariance matrices. The angle plot presents the information loss when moving from the PCA decomposition of one dataset to the PCA decomposition of the other. The chroma plot describes the loading patterns of the two datasets, thereby presenting the relative weighting and importance of the variables from the original dataset.
Maintained by Anne Helby Petersen. Last updated 3 years ago.
data-structuresexploratory-data-visualizationsprincipal-component-analysis
1 stars 3.11 score 13 scripts