hi all,(adsbygoogle = window.adsbygoogle || []).push({});

the situation is this:

i have a conditional PDF [tex]f_{X|(D,S)}(x|d,s)[/tex] and the unconditional PDFs D and S, [tex]f_{D}[/tex], [tex]f_{S}[/tex].

Now, I can marginalize the joint PDF [tex]f_{X,D,S}=f_{X|(D,S)}f_{D}f_{S}[/tex] by integrating over [tex]d[/tex] and [tex]s[/tex] over their respective supports. What I'm really interested in is a distribution parameter of the random variable D, let's call it [tex]p[/tex]. The marginal PDF f_{X}(x|p) is the entity at interest, and for example I could perform MLE to determine the parameter [tex]p[/tex].

My question is as follows: Do you know a method that can do without explicitly calculating the marginal PDF [tex]f_{X}[/tex], i.e. not requiring integration which is computationally slow.

I really do not have a good overview over all the methods in statistics. From the sources that I was able to find, the methods Expectation-maximization algorithm, MCMC method were mentioned frequently but I don't understand how they work and how they can be useful for my problem.

thanks a lot!

**Physics Forums - The Fusion of Science and Community**

Join Physics Forums Today!

The friendliest, high quality science and math community on the planet! Everyone who loves science is here!

The friendliest, high quality science and math community on the planet! Everyone who loves science is here!

# Efficient parameter estimation of marginal distribution

Loading...

Similar Threads - Efficient parameter estimation | Date |
---|---|

I Fitting two models in sequence with parameters in common | Jan 14, 2018 |

Signal vs Bkg efficiency plots | Sep 9, 2015 |

Inverse Efficiency Matrix (error) | Dec 17, 2014 |

Poisson distribution with efficiency problem | Jun 9, 2012 |

Updating the mean and sd of a set efficiently | Sep 1, 2011 |

**Physics Forums - The Fusion of Science and Community**