This R-code is intended for multicriteria decision support problems solved by the Composition of Probabilistic Preferences (CPP), created by Professor Annibal Parracho Sant´Anna. The two functions in this code calculate the joint probabilities of alternatives maximizing (PMax) and minimizing (PMin) their preferences in a criterion. The measures of the problem's decision matrix are the frequencies of responses to the Likert scale values collected by questionnaires. Version 2.0 added the "min" method for ranking ties and error calculation in the example
A straightforward implementation of Myers blended digit preference index in R. The code is tested an...
Data and code to calculate Probability-Density-Ranking (PDR) outliers and Most Probable Range (MPR
<p>Analysis of preference ratings separately for Random and Symmetry patterns.</p
This R-code is intended for multicriteria decision support problems solved by the Composition of Pro...
Abstract This paper aimed at presenting an Empirical Approach to the Composition of Probabilistic Pr...
International audienceIn order to represent the preferences of a group of individuals, we introduce ...
Stated Preference Methods Using R explains how to use stated preference (SP) methods, which are a fa...
AbstractThe Composition of Probabilistic Preferences (CPP) is employed here to combine evaluations o...
Eliciting the preferences of a Decision Maker (DM) is a challenging task in multi criteria-decision ...
This paper proposes a “probabilistic ” extension of conditional preference networks as a way to comp...
A popular discrete choice model that incorporates correlation information is the multinomial probit ...
International audienceThis paper proposes a \probabilistic" extension of conditional preference netw...
We introduce probabilistic lexicographic preference trees (or PrLPTs for short). We show that they o...
There has been great advancement on research for preferential choice in field of marketing. When we ...
In this study, we consider learning preference structure of a Decision Maker (DM). Many preference m...
A straightforward implementation of Myers blended digit preference index in R. The code is tested an...
Data and code to calculate Probability-Density-Ranking (PDR) outliers and Most Probable Range (MPR
<p>Analysis of preference ratings separately for Random and Symmetry patterns.</p
This R-code is intended for multicriteria decision support problems solved by the Composition of Pro...
Abstract This paper aimed at presenting an Empirical Approach to the Composition of Probabilistic Pr...
International audienceIn order to represent the preferences of a group of individuals, we introduce ...
Stated Preference Methods Using R explains how to use stated preference (SP) methods, which are a fa...
AbstractThe Composition of Probabilistic Preferences (CPP) is employed here to combine evaluations o...
Eliciting the preferences of a Decision Maker (DM) is a challenging task in multi criteria-decision ...
This paper proposes a “probabilistic ” extension of conditional preference networks as a way to comp...
A popular discrete choice model that incorporates correlation information is the multinomial probit ...
International audienceThis paper proposes a \probabilistic" extension of conditional preference netw...
We introduce probabilistic lexicographic preference trees (or PrLPTs for short). We show that they o...
There has been great advancement on research for preferential choice in field of marketing. When we ...
In this study, we consider learning preference structure of a Decision Maker (DM). Many preference m...
A straightforward implementation of Myers blended digit preference index in R. The code is tested an...
Data and code to calculate Probability-Density-Ranking (PDR) outliers and Most Probable Range (MPR
<p>Analysis of preference ratings separately for Random and Symmetry patterns.</p