ABSTRACT
In the statistical analysis of time series, measurements of a phenomenon
with uncertainty are considered to be the realization of a random vari-
able that follows a certain probability distribution. Time series models
and statistical models, in general, are built to specify this probability dis-
tribution based on data. In this chapter, a basic criterion is introduced
for evaluating the closeness between the true probability distribution and
the probability distribution specified by a model. Based on this criterion,
we can derive a unified approach for building statistical models includ-
ing the maximum likelihood method and the information criterion, AIC
(Akaike (1973,1974), Sakamoto et al. (1986) and Konishi and Kitagawa
(2008)).
