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- W4312891911 abstract "In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decades." @default.
- W4312891911 created "2023-01-05" @default.
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- W4312891911 date "2021-01-01" @default.
- W4312891911 modified "2023-09-25" @default.
- W4312891911 title "Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate" @default.
- W4312891911 doi "https://doi.org/10.22457/apam.v23n1a04801" @default.
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