Thomas Wieland

Open-source software projects

huff: Market Area Analysis in Python

The huff Python library is designed for performing market area analyses with the Huff Model and/or the Multiplicative Competitive Interaction (MCI) Model, as well as market area and accessibility models derived from or related to them. The package is intended for researchers in economic geography, regional economics, marketing, geoinformation science, and health geography. It is designed to cover the entire workflow of a market area analysis, including model calibration and GIS-related processing.

Availability

Documentation

diffindiff: Python library for convenient Difference-in-Differences analyses

The diffindiff Python library is designed for performing Difference-in-Differences (DiD) analyses in a convenient way. The package is intended to be used in econometric analyses of natural experiments by researchers in economics, marketing, economic geography, and health sciences. It is designed to cover the entire workflow of a DiD analysis, while not requiring extensive programming skills.

Availability

Documentation

Case study (preprint)

swash: Health Geography Toolbox for Model-Based Analysis of Infections Panel Data

Within epidemic outbreaks, infections grow and decline differently between regions, and the velocity of spatial spread differs between countries. The swash library offers a set of model-based analyses for these topics. Spread velocity may be analysed with the Swash-Backwash Model of the Single Epidemic Wave and corresponding functions for bootstrap confidence intervals, country comparison, and visualization of results. Differences in epidemic growth between regions may be analysed using logistic growth models, exponential growth models, Hawkes processes and breakpoint analyses. Cluster and hotspot analyses can be conducted using neighborhood matrices.

Availability

Documentation

Reference manual (CRAN)

C19dNUTS: Dataset of Regional COVID-19 Deaths per 100,000 Pop (NUTS)

Dataset containing cumulative COVID-19 deaths (absolute and per 100,000 pop) at the regional level (mostly NUTS 3) for 31 EU/EFTA countries.

Availability

CRAN

Documentation

Reference manual (CRAN)

MCI2: Market Area Models for Retail and Service Locations

Market area models are used to analyze and predict store choices and market areas concerning retail and service locations. This package is a more user-friendly wrapper of the functions in the package MCI providing market area analysis using the Huff Model or the Multiplicative Competitive Interaction (MCI) Model. In MCI2, also a function for creating transport costs matrices is provided.

Availability

not publicly available

previous CRAN page

REAT: Regional Economic Analysis Toolbox

The REAT package is a collection of models and analysis methods used in regional and urban economics and (quantitative) economic geography. It includes functions from the following seven thematic groups: (1) Inequality, concentration and dispersion indicators, (2) Indicators of specialization of regions and spatial concentration of industries, (3) Analysis of regional disparities and regional convergence, (4) Analysis of regional growth, (5) Spatial interaction and accessibility models, (6) Proximity analysis, and (7) Additional tools for data preparation und visualization.

Availability

CRAN

Documentation

MCI: Multiplicative Competitive Interaction (MCI) Model

Market area models are used to analyze and predict store choices and market areas concerning retail and service locations. This package implements two market area models (Huff Model, Multiplicative Competitive Interaction Model) into R, while the emphases lie on 1.) fitting these models based on empirical data via OLS regression and nonlinear techniques and 2.) data preparation and processing (esp. interaction matrices and data preparation for the MCI Model).

Availability

CRAN

Documentation

Python logo: Python® and the Python logos are trademarks of the Python Software Foundation (PSF). Used to indicate that this package is implemented in Python. This project is not affiliated with or endorsed by the PSF. See the PSF trademark policy.