RT Journal Article
T1 Testing the order of Markov dependence in DNA sequences
A1 Pardo Llorente, Leandro
A1 Menéndez Calleja, María Luisa
A1 Pardo Llorente, María del Carmen
A1 Zografos, Konstantinos
AB DNA or protein sequences are usually modeled as probabilistic phenomena. The simplest model is created on the assumption that the nucleotides at the various sites are independently distributed. Usually the type of nucleotide at some site depends on the type at another site and therefore the DNA sequence is modeled as a Markov chain of random variables taking on the values A, G, C and T corresponding to the four nucleotides. First order or higher order Markov models provide better fit to a DNA sequence. Based on this remark, the aim of this paper is to present and study a family of test statistics for testing order Markov dependence in DNA sequences. This new family includes as a particular case the classical likelihood ratio test. A simulation study is presented in order to find test statistics, in this family, with a better behaviour than the likelihood ratio test.
PB Springer
SN 1387-5841
YR 2011
FD 2011-03
LK https://hdl.handle.net/20.500.14352/42420
UL https://hdl.handle.net/20.500.14352/42420
LA eng
DS Docta Complutense
RD 19 abr 2025