Showing 8 of total 8 results (show query)
appsilon
shiny.semantic:Semantic UI Support for Shiny
Creating a great user interface for your Shiny apps can be a hassle, especially if you want to work purely in R and don't want to use, for instance HTML templates. This package adds support for a powerful UI library Fomantic UI - <https://fomantic-ui.com/> (before Semantic). It also supports universal UI input binding that works with various DOM elements.
Maintained by Jakub Nowicki. Last updated 11 months ago.
appsilonfomantic-uirhinoversesemanticsemantic-componentssemantic-uishiny
506 stars 13.00 score 586 scripts 3 dependents
dreamrs
toastui:Interactive Tables, Calendars and Charts for the Web
Create interactive tables, calendars and charts with 'TOAST UI' <https://ui.toast.com/> libraries to integrate in 'shiny' applications or 'rmarkdown' 'HTML' documents.
Maintained by Victor Perrier. Last updated 28 days ago.
86 stars 10.03 score 144 scripts 8 dependents
pvanlaake
CFtime:Using CF-Compliant Calendars with Climate Projection Data
Support for all calendars as specified in the Climate and Forecast (CF) Metadata Conventions for climate and forecasting data. The CF Metadata Conventions is widely used for distributing files with climate observations or projections, including the Coupled Model Intercomparison Project (CMIP) data used by climate change scientists and the Intergovernmental Panel on Climate Change (IPCC). This package specifically allows the user to work with any of the CF-compliant calendars (many of which are not compliant with POSIXt). The CF time coordinate is formally defined in the CF Metadata Conventions document available at <https://cfconventions.org/Data/cf-conventions/cf-conventions-1.12/cf-conventions.html#time-coordinate>.
Maintained by Patrick Van Laake. Last updated 9 hours ago.
5 stars 9.24 score 48 scripts 15 dependents
nicchr
timeplyr:Fast Tidy Tools for Date and Date-Time Manipulation
A set of fast tidy functions for wrangling, completing and summarising date and date-time data. It combines 'tidyverse' syntax with the efficiency of 'data.table' and speed of 'collapse'.
Maintained by Nick Christofides. Last updated 11 days ago.
40 stars 7.09 score 185 scripts
archaeostat
ArchaeoPhases:Post-Processing of Markov Chain Monte Carlo Simulations for Chronological Modelling
Statistical analysis of archaeological dates and groups of dates. This package allows to post-process Markov Chain Monte Carlo (MCMC) simulations from 'ChronoModel' <https://chronomodel.com/>, 'Oxcal' <https://c14.arch.ox.ac.uk/oxcal.html> or 'BCal' <https://bcal.shef.ac.uk/>. It provides functions for the study of rhythms of the long term from the posterior distribution of a series of dates (tempo and activity plot). It also allows the estimation and visualization of time ranges from the posterior distribution of groups of dates (e.g. duration, transition and hiatus between successive phases) as described in Philippe and Vibet (2020) <doi:10.18637/jss.v093.c01>.
Maintained by Anne Philippe. Last updated 12 months ago.
archaeologybayesian-statisticsgeochronologymarkov-chainradiocarbon-dates
10 stars 6.90 score 66 scripts
aqlt
ggdemetra:'ggplot2' Extension for Seasonal and Trading Day Adjustment with 'RJDemetra'
Provides 'ggplot2' functions to return the results of seasonal and trading day adjustment made by 'RJDemetra'. 'RJDemetra' is an 'R' interface around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System and the European System of Central Banks.
Maintained by Alain Quartier-la-Tente. Last updated 8 months ago.
12 stars 6.06 score 16 scripts 1 dependentsaqlt
ggdemetra3:'ggplot2' Extension for Seasonal and Trading Day Adjustment with 'JDemetra+' 3.0
Provides 'ggplot2' functions to return the results of seasonal and trading day adjustment made by the R interface to 'JDemetra+' 3.0.
Maintained by Alain Quartier-la-Tente. Last updated 3 months ago.
4 stars 4.26 score 8 scripts 1 dependents
gallegoj
tfarima:Transfer Function and ARIMA Models
Building customized transfer function and ARIMA models with multiple operators and parameter restrictions. Functions for model identification, model estimation (exact or conditional maximum likelihood), model diagnostic checking, automatic outlier detection, calendar effects, forecasting and seasonal adjustment. See Bell and Hillmer (1983) <doi:10.1080/01621459.1983.10478005>, Box, Jenkins, Reinsel and Ljung <ISBN:978-1-118-67502-1>, Box, Pierce and Newbold (1987) <doi:10.1080/01621459.1987.10478430>, Box and Tiao (1975) <doi:10.1080/01621459.1975.10480264>, Chen and Liu (1993) <doi:10.1080/01621459.1993.10594321>.
Maintained by Jose L. Gallego. Last updated 1 years ago.
2 stars 4.04 score 11 scripts