34 citations · 76 across the 11 of their papers we have counts for
6 papers · 1 filter
Asymptotics of Monte Carlo maximum likelihood estimators
Blazej Miasojedow, Wojciech Niemiro, Jan Palczewski +1
We describe Monte Carlo approximation to the maximum likelihood estimator in models with intractable norming constants and explanatory variables. We consider both sources of random…
Adaptive Monte Carlo Maximum Likelihood
Blazej Miasojedow, Wojciech Niemiro, Jan Palczewski +1
We consider Monte Carlo approximations to the maximum likelihood estimator in models with intractable norming constants. This paper deals with adaptive Monte Carlo algorithms, whic…
Metropolis-type algorithms for Continuous Time Bayesian Networks
Blazej Miasojedow, Wojciech Niemiro, John Noble +1
We present a Metropolis-Hastings Markov chain Monte Carlo (MCMC) algorithm for detecting hidden variables in a continuous time Bayesian network (CTBN), which uses reversible jumps…
Nonasymptotic bounds on the estimation error of MCMC algorithms
Krzysztof Łatuszyński, Błażej Miasojedow, Wojciech Niemiro
We address the problem of upper bounding the mean square error of MCMC estimators. Our analysis is nonasymptotic. We first establish a general result valid for essentially all ergo…
Rigorous confidence bounds for MCMC under a geometric drift condition
Krzysztof Latuszynski, Wojciech Niemiro
We assume a drift condition towards a small set and bound the mean square error of estimators obtained by taking averages along a single trajectory of a Markov chain Monte Carlo al…
Nonasymptotic bounds on the estimation error for regenerative MCMC algorithms
Krzysztof Latuszynski, Blazej Miasojedow, Wojciech Niemiro
MCMC methods are used in Bayesian statistics not only to sample from posterior distributions but also to estimate expectations. Underlying functions are most often defined on a con…