In fact, as far as I recall from computational physics literature (most likely, it was in Morokoff and Caflisch (1995)), for the sequence of length up to about $6^d$ where $d$ is the dimension of your space, quasi Monte Carlo sequences do not show appreciable gains over the standard pseudo-random number generators. See the encompassing treatment in Niederreiter (1992). My understanding is that the only quasi-Monte Carlo method that allows to take the next sample (or next $N$ samples) easily without trying to figure out their dependence on the previously collected samples is Halton sequence. Otherwise, you will likely miss some parts of your space. With Latin hypercube samples, you have to decide on the number of samples, so that you break your range into either 10 or 20 bins to begin with.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |