random.pcmatrices: A function to obtain random matrices

In iaga/ahpsensitivity: Sensitivity analysis tools for Multicriteria Decision Making methods

Description

A function to obtain random matrices

Usage

random.pcmatrices(data_lower, data_upper, nmatrices)

Arguments

data_lower	A list of dataframes objects with the lower bounds for each pairwise comparison matrix
data_upper	A list of dataframes objects with the upper bounds for each pairwise comparison matrix
nmatrices	Integer, total number of random matrices to generate

Value

A list of matrices

Details

Given matrices

C^{L} = ≤ft[ {\begin{array}{cccc} 1 & a^L_{12} & … & a^L_{1m}\\ 1/a^L_{12} & 1 & … & a^L_{2m} \\ … & … & 1 & …\\ 1/a^L_{1m} & 1/a^L_{2m} & … & 1 \end{array} } \right],\hspace{.5cm} C^{U} = ≤ft[ {\begin{array}{cccc} 1 & a^U_{12} & … & a^U_{1m}\\ 1/a^U_{12} & 1 & … & a^U_{2m} \\ … & … & 1 & …\\ 1/a^U_{1m} & 1/a^U_{2m} & … & 1 \end{array} } \right]

with the lower and upper bounds of an interval pairwise comparison matrix, this function generates a set of random matrices within the interval. The random numbers for each comparison are generated with an uniform distribution.

References

Saaty, Thomas L. y Vargas, Luis G.: Uncertainty and rank order in the analytic hierarchy process. European Journal of Operational Research, 1987, 32(1), pp. 107–117. ISSN 0377- 2217. doi: 10.1016/0377-2217(87)90275-X.

See Also

runif about the uniform distribution

iaga/ahpsensitivity documentation built on Dec. 20, 2021, 5:57 p.m.