Calculate and Visualize the Herfindahl-Hirschman Index
Based on the aggregated shares retained by individual firms or actors within a market or space, the Herfindahl-Hirschman Index (HHI) measures the level of concentration in the market or space. It is often used as a measure of competition, where 0 equals perfect competition amongst firms or actors and 10,000 equals perfect monopoly. This package allows for intuitive and straightforward computation of the HHI, requiring placement of objects directly into the function, including the data frame first, followed by the name of the vector (or variable) corresponding with the market shares in quotation marks. The package also includes a plot function for quick visual display of HHI time series across any measure of time (year, quarter, month, etc.) Suggested citation of the HHI: Rhoades, Stephen A. (1993, "The herfindahl-hirschman index." Federal Reserve Bulletin 79: 188).

Based on the aggregated shares retained by individual firms or actors within a market or space, the Herfindahl-Hirschman Index (HHI) measures the level of concentration in a space. This package allows for intuitive and straightforward computation of HHI scores, requiring placement of objects of interest directly into the function. The package also includes a plot function for quick visual display of an HHI time series using any measure of time (year, quarter, month, etc.). For usage, please cite the Journal of Open Source Software paper associated with the package: Waggoner, Philip D. (2018) <doi:10.21105/joss.00828>.

Hidden Hybrid Markov/Semi-Markov Model Fitting
Develops algorithms for fitting, prediction, simulation and initialization of the hidden hybrid Markov/semi-Markov model, introduced by Guedon (2005) <doi:10.1016/j.csda.2004.05.033>.

Develops algorithms for fitting, prediction, simulation
and initialization of the hidden hybrid Markov/semi-Markov model,
introduced by Guedon (2005) <doi:10.1016/j.csda.2004.05.033>,
which also includes several tools for handling missing data,
fitting regime sweaching regression and auto-regressive
hidden hybrid Markov/semi-Markov model, and many other useful tools.