Although epistasis is an important phenomenon in the genetics and evolution of complex traits, epistatic effects are hard to estimate. The main problem is due to the overparameterized epistatic ...
Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...
In multiple change-point problems, different data segments often follow different distributions, for which the changes may occur in the mean, scale or the entire distribution from one segment to ...
Proceedings of the National Academy of Sciences of the United States of America, Vol. 108, No. 19 (May 10, 2011), pp. 7860-7865 (6 pages) The substitution rate in a gene can provide valuable ...
We present a maximum-likelihood method for parameter estimation in terahertz time-domain spectroscopy. We derive the likelihood function for a parameterized frequency response function, given a pair ...
The challenge of using small sample sizes for operational risk capital models fitted via maximum likelihood estimation is well recognized, yet the literature generally provides warning examples rather ...
Our method can be used to train implicit probabilistic models (a common example being the generator in GANs). Unlike GANs, however, our method does not suffer from mode collapse/dropping and is stable ...
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