Imports: crayon, grDevices, limSolve, magrittr, stringr, utils
Packaged: 2018-11-28 08:17:52 UTC; H.G. van den Boorn

Imports: crayon, dplyr, grDevices, limSolve, magrittr, stats, stringr,
Packaged: 2019-09-07 13:12:04 UTC; H.G. van den Boorn

Title: Hierarchical and Geographically Weighted Regression
Description: This model divides coefficients into three types,
i.e., local fixed effects, global fixed effects, and random effects.
If data have spatial hierarchical structures (especially are overlapping on some locations),
it is worth trying this model to reach better fitness.

i.e., local fixed effects, global fixed effects, and random effects (Hu et al., 2022)<doi:10.1177/23998083211063885>.

Author: Yigong Hu, Richard Harris, Richard Timmerman

Title: HHCART(G) - A Reflected Feature Space for CART
Authors@R: person("Phil", "Davies", email="phil.davies@pg.canterbury.ac.nz", role=c('aut','cre'))
Description: An implementation of the HHCART-G algorithm as described in the
paper - Wickramarachchi C, Robertson B, Reale M, Price C, Brown J (2019). 'A
reflected feature space for CART.' Australian & New Zealand Journal of Statistics,
Imports: checkmate, hash, Matrix, DiagrammeR, ggplot2, DiagrammeRsvg,

Title: Age-Structured Spatio-Temporal Models for Infectious Disease
Description: Meyer and Held (2017) <doi:10.1093/biostatistics/kxw051> present an
age-structured spatio-temporal model for infectious disease counts. The
approach is illustrated in a case study on norovirus gastroenteritis in
Berlin, 2011-2015, by age group, city district and week, using additional
contact data from the POLYMOD survey. This package contains the data and
code to reproduce the results from the paper, see 'demo("hhh4contacts")'.
Suggests: MASS, lattice, gridExtra, scales, numDeriv

Title: Calculate and Visualize the Herfindahl-Hirschman Index
Author: Philip D. Waggoner <philip.waggoner@gmail.com>
Maintainer: Philip D. Waggoner <philip.waggoner@gmail.com>
Description: 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).