Beta regression model is a widely known statistical model when the response variable has
the form of fractions or percentages. The maximum likelihood method is usually employed …

Weibull regression model is one of the most prevalently used parametric regression models.
Estimation of the parameters of this model is affected by the presence of outliers. Outliers …

One-parameter exponential regression is one of the most common and widely used models
in several fields, to estimate the parameters of the one-parameter exponential regression …

Regression analysis plays a vital role in many areas of science. Almost all regression
analyses rely on the method of least squares for estimation of the parameters in the model …

In regression analysis the use of least squares method would not be appropriate in solving
problem containing outliers or extreme observations. So, we need alternative method which …

The primary approach for obtaining regression parameters in the beta regression model is
the utilization of the maximum likelihood estimation technique. However, it is acknowledged …

Independence of error terms in a linear regression model, often not established. So a linear
regression model with correlated error terms appears in many applications. According to the …

The multiple linear regression modelsare one of the important models in regression
because it is used in analyzing a lot of data in various economic, medical and social fields …

Exponential regression is one of the most common and widely used models in several fields
to estimate the parameters of the exponential regression model using ordinary nonlinear …

The regression model estimator is considered efficient if it is robust and resistant to the
presence of heteroscedasticity variance, multicollinearity or unusual observations called …