Mixed Stereographic Circular Probability Model: A comparative study using M. L Estimation

Now a days, circular statistics has a wide range of applications in the fields of Engineering, Geosciences, Environmental studies, Medicine, Psychology, Economics and Finance etc., such as analyzing angular movements in robotics, orientations in structural Engineering, Seismic wave directions, water and air flow patterns, brain waves in EEG signals, eye ball movements, modeling of economic indicators behaviors which cannot be analyzed using linear statistical methods as the data involves periodic nature. Many researchers have presented discrete and continuous circular probability models; their properties are discussed. By combining two distinct probability distributions rather than utilizing a single probability model, the T-X family of probability distributions is intended to increase the efficiency and reduce errors. We developed a mixed stereographic circular probability model with this interest. Study is done on same attributes. The maximum likelihood estimators, AIC and BIC values were determined in this study. The model’s output is compared with those of the current existing single circular probability models by using an eye data set from a glaucoma clinic at the University of Malaya Medical Centre in Malaysia.