Comparative estimation models, Bayesian and iterative on the effect of consumption indicators on inflation in Algeria

Abstract EN

The estimation of parameters in iterative models is affected by the probabilistic event, while Bayesian estimation is based on conditional probability theory that explains the phenomenon according to the theory of random states and Markov chains.

as the aim of the study is to identify the difference between the iterative and Bayesian analysis model of the impact of price indicators in Algeria on inflation, relying on the descriptive analytical.

which revealed the correlation between inflation and the food consumption index as a single indicator using iterative inference, while it was associated with a more overlapping relationship using Bayesian inference.

making it a significant models.