In a recent paper, Qi Ding et al [3] formulated an approach to determine a linear regression model for DNA sequences. By regarding a DNA primary sequence as a random process in time and defining the nucleotides' random distribution functions in three ways based on chemical structures they proposed two methods to measure their similarities. Relating the random distribution functions by a linear regression equation enabled them to construct six new models to analyse the DNA sequences and quantify their similarities and dissimilarities. The optimal model can be chosen based on the amount of information contained or lost in the process.