Timeline for How to sample from a joint probability distribution of two variables? [duplicate]
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| Apr 12, 2021 at 22:13 | history | duplicates list edited | whuber♦ | duplicates list edited from How to generate numbers based on an arbitrary discrete distribution? to How to generate numbers based on an arbitrary discrete distribution?, How to sample from a discrete distribution? [duplicate] | |
| Apr 12, 2021 at 22:12 | history | closed | whuber♦ probability Users with the probability badge or a synonym can single-handedly close probability questions as duplicates and reopen them as needed. | Duplicate of How to generate numbers based on an arbitrary discrete distribution? | |
| Apr 12, 2021 at 22:11 | comment | added | whuber♦ | This is a discrete distribution with 5000 members in the state space. | |
| Apr 12, 2021 at 22:11 | comment | added | fblundun | If each random variable has a finite set of possible values then it's a joint probability mass function rather than a joint probability density function. It sounds like you know the exact probability of each of the 5000 possible outcomes, in which case you could just use numpy.random.choice (stackoverflow.com/a/26196078) or an equivalent algorithm to draw each sample - no need to use MCMC. | |
| Apr 12, 2021 at 21:14 | comment | added | leo31 | So, in the data, the variable x ranges from 1 to 50 and variable y ranges from 1 to 100. I have it in matrix form where each cell has a probability value associated with the (x,y) pair. I do not think this could be considered as a 50-variate distribution. | |
| Apr 12, 2021 at 20:59 | comment | added | jcken | Can you put some more context in? Is it possible to write the density down? MCMC can be a very inefficient sampler in many cases | |
| Apr 12, 2021 at 20:57 | comment | added | Dave | What is dimension 100x50? Do you mean 100 observations of a 50-variate distribution? | |
| Apr 12, 2021 at 20:55 | review | First posts | |||
| Apr 12, 2021 at 22:12 | |||||
| Apr 12, 2021 at 20:54 | history | asked | leo31 | CC BY-SA 4.0 |