Multi-Criteria Decision Making Methods for Crisp Data
Implementation of several MCDM methos for crisp data for decision
making problems. The methods that are implemented in this package are RIM,
TOPSIS (with two normalization procedures), VIKOR, Multi-MOORA and WASPAS.
In addition, MetaRanking function calculates a new ranking from the sum
of the rankings calculated, as well as an aggregated ranking.

Elizabeth Koehler <e.koehler@vanderbilt.edu> and Sebastien Haneuse
This package has functions to estimate Monte Carlo error in simulation studies.  It also has functions that help with planning the number of replications required in a simulation study to reach a specified level of certainty.

Elizabeth Koehler <e.koehler@vanderbilt.edu> and Sebastien
Haneuse
This package has functions to estimate Monte Carlo error
in simulation studies.  It also has functions that help with
planning the number of replications required in a simulation
study to reach a specified level of certainty.

Multiplicative Competitive Interaction (MCI) Model
The Multiplicative Competitive Interaction (MCI) Model by Nakanishi & Cooper (1974) <DOI:10.2307/3151146> is an econometric model for analyzing market shares and/or market areas. The functions in this package include fitting the MCI model, the log-centering transformation of MCI datasets and tools for data preparation.

The Multiplicative Competitive Interaction (MCI) Model by Nakanishi & Cooper (1974) <DOI:10.2307/3151146> is an econometric model for analyzing market shares and/or market areas. The functions in this package include fitting the MCI model, MCI shares simulations, the log-centering transformation of MCI datasets, creation of interaction matrices and tools for data preparation.

The Multiplicative Competitive Interaction (MCI) Model by Nakanishi & Cooper (1974) <DOI:10.2307/3151146> is an econometric model for analyzing market shares and/or market areas and is closely related to the Huff model. The functions in this package include fitting the MCI model, MCI shares simulations, the log-centering transformation of MCI datasets, creation of interaction matrices and tools for data preparation. Additionally, the package provides applications for the Huff model, including a non-linear fitting algorithm.