For random walk, there are entropy based tests (Robinson 1991), or you could empirically test the hypothesis by generating random normal data with the same mean and standard deviation and looking at the distribution of your quantiles. You could make generic statements also about whether or not the data demonstrates autocorrelation function values which are not significant and do not appear to have trend. Further, In a random walk, a binary variable for whether or not values are above and below the mean should follow a binomial distribution of size 1 with a probability of .5, there are tests which do this but also take magnitude into account. I mean to say there are a lot of ways to approach that problem, it depends on the application and how strong you want your conclusions to be. What kind of Markov process?
On Sep 3, 2554 BE, at 9:59 PM, Jumlong Vongprasert <jumlong.u...@gmail.com> wrote: > Dear All > I want to test my data for Random Walk or Markov Process. > How I can do this. > Many Thanks > > -- > Jumlong Vongprasert Assist, Prof. > Institute of Research and Development > Ubon Ratchathani Rajabhat University > Ubon Ratchathani > THAILAND > 34000 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
