# [?] Use seed random method for Empirical Distribution for RandomVariate?

Posted 1 month ago
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 Hello My name is Decha. I have question for " seed random method for Empirical Distribution for RandomVariate[dist]Sample as follow Wolfram document. data={3,9,3,6,0,0,5,1,3,9,7,8,3,5,3,2}; FindDistributionParameters[data,NormalDistribution[a,b]] Map[BlockRandom[SeedRandom[1, Method -> #]; RandomVariate[NormalDistribution[a,b]]] &, {"Congruential", "ExtendedCA", "Legacy", "MersenneTwister", "MKL", "Rule30CA"}] It is ok. But for Empirical. it can not use. It can't work with Map of {"Congruential", "ExtendedCA", "Legacy","MersenneTwister", "MKL", "Rule30CA"}It works only with data={3,9,3,6,0,0,5,1,3,9,7,8,3,5,3,2}; dist = EmpiricalDistribution[data] SeedRandom[7, Method -> ExtendedCA] RandomVariate[dist] I must change ExtendedCA to Legacy and to MersenneTwister. only one. It can't work with Map like a NormalDist or other.Who know Map of random seed can work with Empirical Dist?Thank you.Decha
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Posted 1 month ago
 Documentation for SeedRandom mentions 6 "typical" random generators: Congruential, ExtendedCA, Legacy, MersenneTwister, MKL and Rule30CA.The first, Congruential, does not seem to work well with RandomVariate[EmpiricalDistribution[data]]. In fact the kernel dies during evaluation.But the last 5 works: data = {3, 9, 3, 6, 0, 0, 5, 1, 3, 9, 7, 8, 3, 5, 3, 2}; In[2]:= Table[SeedRandom[1, Method -> k]; RandomVariate[EmpiricalDistribution[data]], {k, {"ExtendedCA", "Legacy", "MersenneTwister", "MKL", "Rule30CA"}} ] Out[2]= {8, 5, 3, 8, 3} In another form, using Map: In[3]:= Map[(SeedRandom[1, Method -> #]; RandomVariate[EmpiricalDistribution[data]]) &, {"ExtendedCA", "Legacy", "MersenneTwister", "MKL", "Rule30CA"} ] Out[3]= {8, 5, 3, 8, 3}