在生物技術與基因工程的領域中，連續時間的馬可夫隨機過程常被使用來描述DNA序列上某一個位置之核?酸隨時間變化的情形，並假設DNA序列上不同位置的鹼基之間互相獨立。而當我們考慮DNA序列上不同位置的鹼基之間存在相關性時，根據獨立的假設之下所得到的統計推論可能是不正確的。 本論文除了簡介幾個常見的鹼基替換模型外，更利用Royall與Tsou (2003)提出的強韌概似函數法，將多項分配模型做適當之修正後，使得在序列長度夠長的情況下得到正確的統計推論。 In the fields of biotechnology and genetic engineering, continuous-time Markov chains are commonly used to describe probabilities of mutational events. The nucleotide sites in the DNA are usually assumed to be evolving independently of each other. We investigate the impacts on inference of correlation between bases at different positions in the DNA sequence. We also recommend using the robust likelihood methodology proposed by Royall and Tsou (2003) to convert the multinomial model to become robust against the misspecification of correlation. The adjusted robust multinomial likelihood could automatically incorporate the correlation structure and deliver legitimate inference.
