Why PolicyPortfolios? A policy portfolio is a collection of simple assessments of the presence or absense of state intervention in a specific area (Target) using a concrete state capacity (Instrument). How specific or general the area is, is up to the researcher. How broad or restricted is the collection of assessments is also up to the researcher (Adam, Knill, and Fernandez-i-Marín 2017). Using policy portfolios as objects of analysis allows political science to standardize comparitive policy analysis by providing a common ground of policy intervention, and represents a first step of comparing state intervention in different fields of public life.
PolicyPortfolios is an R package aimed at providing tools for managing, measuring and visualizing policy portfolios. It simplifies the creation of data structures suitable for dealing with policy portfolios, that is, two-dimensional spaces of policy instruments and policy targets. It allows to generates measures of their characteristics and facilitates its visualization.
Development PolicyPortfolios is developed in github.
Raise an issue, being either a bug report, a question on how to use specific functions, a request for improvement, a clarification, ask for documentation or provide ideas.
ggmcmc is an R package aimed at providing tools for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis. The package also facilitates the graphical interpretation of models by providing flexible functions to plot the results against observed variables.
Development ggmcmc is developed in github and has attracted attention from several fields of science.
Raise an issue, being either a bug report, a question on how to use specific functions, a request for improvement, a clarification, ask for documentation or provide ideas.
Introduction This tutorial shows how to process the dataset of institutional characteristics of regulatory agencies in R. It presents the dataset presented at the journal article entitled “Agency proliferation and the globalization of the regulatory state: Introducing a data set on the institutional features of regulatory agencies”, by Jacint Jordana, Xavier Fernández-i-Marín and Andrea C. Bianculli, published at Regulation & Governance (December 2018).
The necessary packages in R to follow the instructions are the following:
Book to be used as a teaching resource for an introductory course on data sources and indicators for international relations and comparative politics.
This paper asks whether strong bureaucracies can effectively constrain the continuously growing stock of rules in modern democracies through organizational coordination and learning. To answer this question, the paper analyzes the growth of rule …
There is a pdf version of Using the ggmcmc package.
Why ggmcmc? ggplot2, based on the grammar of graphics (Wilkinson et al. 2005), empowers R users by allowing them to flexibly crate graphics (Wickham 2009). Based on this idea, ggmcmc is aimed at bringing the design and implementation of ggplot2 to MCMC diagnostics, allowing Bayesian inference users to have better and more flexible visual diagnostic tools.
ggplot2 is based on the idea that the input of any graphic is a data frame mapped to aesthetic attributes (colour, size) of geometric objects (points, lines).