We propose a simple method of constructing quasi-likelihood functions for dependent data based on conditional-mean–variance relationships, and apply the method to estimating the fractal dimension from box-counting data. Simulation studies were carried out to compare this method with the...

Forecasting stock market movements is a challenging task from the practitioners' point of view. We explore how model selection via the least absolute shrinkage and selection operator (LASSO) approach can be better used to forecast stock closing prices using real-world datasets of daily stock...

We consider rank regression for clustered data analysis and investigate the induced smoothing method for obtaining the asymptotic covariance matrices of the parameter estimators. We prove that the induced estimating functions are asymptotically unbiased and the resulting estimators are strongly...