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- Pareto set given an evenly distributed set of parameters, a property which the popular method...
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- distributions – the part of the distributions representing large but rare events – and by the difficulty ... produce substantially inaccurate estimates of parameters for power-law distributions, and even in cases where...
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- Nimrod/G can directly execute large-scale distributed parameter sweep and Monte-Carlo computational experiments. Nimrod/G...
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- dependent samples from the posterior distribution of the parameters...
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- methods to estimate the posterior distribution of model parameters...
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- probability distribution or density functions, and the locally maximal posterior probability parameters. We rate ... distribution function w.r.t. the data, obtained by marginalizing over all the parameters. Approximation is necessitated...
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- distributed according to the one-parameter Mittag-Leffler distribution with index (or exponent) beta...
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- random number generators from GBS distributions. Parameter estimates for censored and uncensored data can also...
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- kinds of nodes (probability distributions), exact and approximate inference, parameter and structure learning, and static...
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- methods concerning the estimation of the distribution parameters are described and implemented. It is also ... models when we assume the random errors distributed according to an exponential power distribution...
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- hyperopt: Distributed Asynchronous Hyper-parameter Optimization. Hyperopt is a Python library for serial and parallel...
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- discussions are devoted to model construction, smoothing parameter selection, computation, and asymptotic convergence. Most ... PLUS language. Code for regression has been distributed in the R package gss freely available...
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- speed distributions, in two methods; Airfoil redesign by interactive modification of geometric parameters; Blending ... polar save files; Plotting of geometry, pressure distributions, and multiple polars...
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- pseudorandom numbers. For a particular choice of parameters, the algorithm provides a super astronomical period ... characteristic polynomial has many terms. The distribution up to v bits accuracy...
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- rational expression of a parameter of the distribution named as the standard deviation. However, normalizing ... constants of many interesting stasistical distributions do not have such closed expressions. The holonomic gradient ... evaluate normalizing constant numerically for several parameters in the framework of Zeilberger’s holonomic systems ... constants are holonomic functions with respect to parameters. Then, such normalizing constants satisfy holonomic systems...
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- Model with Stochastic Volatility and Time-Varying Parameters. R/C++ implementation of the model proposed ... with a focus on generating posterior predictive distributions...
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- full Bayesian inference. A wide range of distributions and link functions are supported, allowing users ... more. In addition, all parameters of the response distribution can be predicted in order...
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- models in a Bayesian framework. The distribution parameters may capture location, scale, shape...
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- null values and the parameters of the null distribution are adaptively estimated from the data...
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- gamma distributions in which the mixing occurs over the shape parameter. This family provides ... requires to specify a prior distribution for a single parameter...