The recent studies suggest that mathematical programming could be a good alternative to the conventional statistical analysis methods as the least squares method and the least absolute method. In fact, the mathematical programming models provide more flexibility for modelling the estimation context. This flexibility gives to the analyst a platform where his knowlege and experience can be an integral part of the parameters estimation.
Moreover, the mathematical programming gives the possibility to take in account the imprecision associated with some variable values. This paper suggests an estimation model which enables the analyst to integrate his experience and judgement in a context where the values of the dependant variable are imprecise and expressed by an interval.
- Goal Programming model
- Imprecise Goals
- Statistical Estimation
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Aouni, B., Kettani, O., Martel, JM. (1997). Estimation Through the Imprecise Goal Programming Model. In: Caballero, R., Ruiz, F., Steuer, R. (eds) Advances in Multiple Objective and Goal Programming. Lecture Notes in Economics and Mathematical Systems, vol 455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46854-4_13
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