Showing 7 of total 7 results (show query)
kevinsblake
NatParksPalettes:Color Palettes Inspired by National Parks
Color palettes for data visualization inspired by National Parks. Currently contains 15 color schemes and checks for colorblind-friendliness of palettes.
Maintained by Kevin Blake. Last updated 2 months ago.
colorpalettedata-visualization
10.0 match 242 stars 6.53 score 281 scripts
birdumbrella
LSD:Lots of Superior Depictions
Create lots of colorful plots in a plethora of variations. Try the LSD demotour().
Maintained by Bjoern Schwalb. Last updated 5 years ago.
8.6 match 2 stars 5.03 score 448 scripts 4 dependents
koenderks
aRtsy:Generative Art with 'ggplot2'
Provides algorithms for creating artworks in the 'ggplot2' language that incorporate some form of randomness.
Maintained by Koen Derks. Last updated 7 hours ago.
3.0 match 174 stars 7.52 score 59 scripts
jamovi
jmvcore:Dependencies for the 'jamovi' Framework
A framework for creating rich interactive analyses for the jamovi platform (see <https://www.jamovi.org> for more information).
Maintained by Jonathon Love. Last updated 6 months ago.
3.0 match 4 stars 6.51 score 20 scripts 8 dependents
helske
seqHMM:Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series
Designed for fitting hidden (latent) Markov models and mixture hidden Markov models for social sequence data and other categorical time series. Also some more restricted versions of these type of models are available: Markov models, mixture Markov models, and latent class models. The package supports models for one or multiple subjects with one or multiple parallel sequences (channels). External covariates can be added to explain cluster membership in mixture models. The package provides functions for evaluating and comparing models, as well as functions for visualizing of multichannel sequence data and hidden Markov models. Models are estimated using maximum likelihood via the EM algorithm and/or direct numerical maximization with analytical gradients. All main algorithms are written in C++ with support for parallel computation. Documentation is available via several vignettes in this page, and the paper by Helske and Helske (2019, <doi:10.18637/jss.v088.i03>).
Maintained by Jouni Helske. Last updated 2 years ago.
categorical-dataem-algorithmhidden-markov-modelshmmmixture-markov-modelstime-seriesopenblascppopenmp
2.3 match 97 stars 8.51 score 92 scripts 1 dependents
cran
rasterImage:An Improved Wrapper of image()
This is a wrapper function for image(), which makes reasonable raster plots with nice axis and other useful features.
Maintained by Martin Seilmayer. Last updated 5 years ago.
3.0 match 2.08 score 4 dependentscran
oaPlots:OpenAnalytics Plots Package
Offers a suite of functions for enhancing R plots.
Maintained by Jason Waddell. Last updated 9 years ago.
1.6 match 1.00 score