@article{MAKHILLJEAS2019141918503,
    title = {Comparison of Estimate Methods of Multiple Linear Regression Model with
Auto-Correlated Errors when the Error Distributed with General Logistic},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {19},
    pages = {7072-7076},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.7072.7076},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.7072.7076},
    author = {Ebtisam,Ahmed D. and},
    keywords = {Autocorrelation,generalized least squares method,Laplace robust method,logistic distribution,M robust method,multiple linear regression},
    abstract = {In this research, we studied the multiple linear regression models for two variables in the presence
of the autocorrelation problem for the error term observations and when the error is distributed with general
logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship
between the variables and through this relationship, the forecasting is completed with the variables as values.
A simulation technique is used for comparison methods depending on the mean square error criteria in where
the estimation methods that were used are (generalized least squares, M robust and Laplace) and for different
sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best method for all values
of correlation coefficients as (Φ = -0.9, -0.5, 0.5, 0.9). So, we applied it to the data that was obtained from the
Ministry of Planning in Iraq/Central Organization for Statistics which represents the consumer price index for
the years 2004-2016. So, we confirmed that the dollar exchange rate is directly affected by the increase in annual
inflation rates and the ratio of currency to the money supply.}
    }