Using the Theory of Belief Functions
Add some elements of 0 mass to an existing basic chance assignment.
Basic chance assignment mass function
Computer norm between two basic chance assignment objects
Simple printing of the tt matrix and mass values of a basic chance a...
Print summary statistics of large mass functions
Representation of a mass function in a product space
Truncation of a basic chance assignment mass function
Calculation of the degrees of Belief and Plausibility of a basic chanc...
Evaluate A, B errors
Calculate belief, disbelief, unknown, plausibility, plausibility ratio
Calculate belief, disbelief, unknown, plausibility, plausibility ratio...
Compute belief, disbelief, unknown, plausibility, plausibility ratio b...
Calculation of the degrees of Belief and Plausibility of a basic chanc...
Plot belplau matrix
Compute qq from tt
Find the value in base 10 of a number coded in another base
Construct subsets names from column names of a tt matrix
Generalized inner product of two matrices
Remove duplicate rows in a two-dimensional table.
Combination of two mass functions
Combination of two mass functions with logsumexp
Manipulation and combination of belief functions
Reduction of a relation
Convert a value to its representation in another chosen base
Extension of the frame of discernment of a variable
Extension of a relation
Intersection of two tables of propositions
Intersect two vectors of ssnames
Adding small probabilities
Transformation of an array data to its matrix representation
Transformation of the tt matrix of a relation
Construct m vector of a bca from marginal probabilities
Construct a mass vector from qq function.
Construct a mass vector from qq function and ttmatrix of focal element...
Mobius inversion of commonality function
Naming the columns of the tt matrix of a product space
Naming the columns of the tt matrix
Combining the column names of a matrix to construct names for the rows
Normalization of a basic chance assignment
Normalization of a basic chance assignment with logsumexp
The peeling algorithm
Plausibility transformation of the singletons of a frame
Product space representation of a relation
Summary of a vector for any operator.
Obtain dimensions of an array or length of a vector with a single comm...
Prepare a table of results
Construct a description matrix from a list of subsets names.
Construct tt matrix of a bca from marginal probabilities
Construct a description matrix from qq function.
Create partition matrix
Using the Theory of Belief Functions for evidence calculus. Basic probability assignments, or mass functions, can be defined on the subsets of a set of possible values and combined. A mass function can be extended to a larger frame. Marginalization, i.e. reduction to a smaller frame can also be done. These features can be combined to analyze small belief networks and take into account situations where information cannot be satisfactorily described by probability distributions.