منابع مشابه
Maximum-likelihood density modification
A likelihood-based approach to density modification is developed that can be applied to a wide variety of cases where some information about the electron density at various points in the unit cell is available. The key to the approach consists of developing likelihood functions that represent the probability that a particular value of electron density is consistent with prior expectations for t...
متن کاملMaximum-likelihood density modification using pattern recognition of structural motifs
The likelihood-based approach to density modification [Terwilliger (2000), Acta Cryst. D56, 965-972] is extended to include the recognition of patterns of electron density. Once a region of electron density in a map is recognized as corresponding to a known structural element, the likelihood of the map is reformulated to include a term that reflects how closely the map agrees with the expected ...
متن کاملMaximum likelihood kernel density estimation
Methods for improving the basic kernel density estimator include variable locations, variable bandwidths (often called variable kernels) and variable weights. Currently these methods are implemented separately and via pilot estimation of variation functions derived from asymptotic considerations. In this paper, we propose a simple maximum likelihood procedure which allows (in its greatest gener...
متن کاملA Universally Consistent Modification of Maximum Likelihood
In some models, both parametric and not, maximum likelihood estimation fails to be consistent. We investigate why the maximum likelihood method breaks down with some examples and notice the paradox that, in those same models, maximum likelihood estimation would have been consistent if the data had been measured with error. With this motivation we define doubly-smoothed maximum likelihood as a n...
متن کاملMaximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation
The paper considers sequential prediction of individual sequences with log loss (online density estimation) using an exponential family of distributions. We first analyze the regret of the maximum likelihood (“follow the leader”) strategy. We find that this strategy is (1) suboptimal and (2) requires an additional assumption about boundedness of the data sequence. We then show that both problem...
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ژورنال
عنوان ژورنال: Acta Crystallographica Section D Biological Crystallography
سال: 2000
ISSN: 0907-4449
DOI: 10.1107/s0907444900005072