networkD3 - D3 JavaScript Network Graphs from R

Creates 'D3' 'JavaScript' network, tree, dendrogram, and Sankey graphs from 'R'.

Last updated 6 years ago

d3jsnetworks

13.52 score 651 stars 34 packages 2.8k scripts 17k downloads

DataCombine - Tools for Easily Combining and Cleaning Data Sets

Tools for combining and cleaning data sets, particularly with grouped and time series data. This includes functions for merging data while reporting duplicates, filling in columns with values of a column in another data frame, and creating continuous time data for interupted time series.

Last updated 4 years ago

8.43 score 55 stars 2 packages 784 scripts 10k downloads

repmis - Miscellaneous Tools for Reproducible Research

Tools to load 'R' packages and automatically generate BibTeX files citing them as well as load and cache plain-text and 'Excel' formatted data stored on 'GitHub', and from other sources.

Last updated 9 years ago

7.44 score 24 stars 9 packages 426 scripts 972 downloads

d3Network - The Old Package for Creating D3 JavaScript Network, Tree, Dendrogram, and Sankey Graphs

!!! NOTE: Active development has moved to the networkD3 package. !!!

Last updated 10 years ago

6.62 score 171 stars 82 scripts 427 downloads

simPH - Simulate and Plot Estimates from Cox Proportional Hazards Models

Simulates and plots quantities of interest (relative hazards, first differences, and hazard ratios) for linear coefficients, multiplicative interactions, polynomials, penalised splines, and non-proportional hazards, as well as stratified survival curves from Cox Proportional Hazard models. It also simulates and plots marginal effects for multiplicative interactions. Methods described in Gandrud (2015) <doi:10.18637/jss.v065.i03>.

Last updated 3 years ago

6.22 score 14 stars 47 scripts 492 downloads

dpmr - Data Package Manager for R

Create, install, and summarise data packages that follow the Open Knowledge Foundation's Data Package Protocol.

Last updated 7 years ago

4.45 score 56 stars 5 scripts 147 downloads

mcreplicate - Multi-Core Replicate

Multi-core replication function to make it easier to do fast Monte Carlo simulation. Based on the mcreplicate() function from the 'rethinking' package. The 'rethinking' package requires installing 'rstan', which is onerous to install, while also not adding capabilities to this function.

Last updated 3 years ago

parallel-computingsimulation

4.16 score 5 stars 29 scripts 172 downloads

coreSim - Core Functionality for Simulating Quantities of Interest from Generalised Linear Models

Core functions for simulating quantities of interest from generalised linear models (GLM). This package will form the backbone of a series of other packages that improve the interpretation of GLM estimates.

Last updated 8 years ago

generalised-linear-modelsglmsimulating-quantitiessimulation

3.88 score 5 stars 1 packages 9 scripts 264 downloads

plotMElm - Plot Marginal Effects from Linear Models

Plot marginal effects for interactions estimated from linear models.

Last updated 6 years ago

3.54 score 7 stars 7 scripts 143 downloads

simpleSetup - Set Up R Source Code Files for Use on Multiple Machines

When working across multiple machines and, similarly for reproducible research, it can be time consuming to ensure that you have all of the needed packages installed and loaded and that the correct working directory is set. 'simpleSetup' provides simple functions for making these tasks more straightforward.

Last updated 8 years ago

3.00 score 1 stars 20 scripts 126 downloads

dynsim - Dynamic Simulations of Autoregressive Relationships

Dynamic simulations and graphical depictions of autoregressive relationships.

Last updated 3 years ago

2.70 score 1 stars 4 scripts 287 downloads

pltesim - Simulate Probabilistic Long-Term Effects in Models with Temporal Dependence

Calculates and depicts probabilistic long-term effects in binary models with temporal dependence variables. The package performs two tasks. First, it calculates the change in the probability of the event occurring given a change in a theoretical variable. Second, it calculates the rolling difference in the future probability of the event for two scenarios: one where the event occurred at a given time and one where the event does not occur. The package is consistent with the recent movement to depict meaningful and easy-to-interpret quantities of interest with the requisite measures of uncertainty. It is the first to make it easy for researchers to interpret short- and long-term effects of explanatory variables in binary autoregressive models, which can have important implications for the correct interpretation of these models.

Last updated 7 years ago

simulationtime-seriesvisualization

2.70 score 1 stars 6 scripts 484 downloads