Ranjan. Effi- cient optimization of the likelihood function in gaussian processButler, A., Haynes, R. D., Humphries, T. D., and Ranjan, P. (2014), "Efficient Opti- mization of the Likelihood Function in Gaussian Process Modelling," Computational Statistics & Data Analysis, 73, 40-52....
The Log Marginal Likelihood refers to the logarithm of the marginal likelihood function, which is maximized to obtain the optimal set of hyperparameters in Gaussian Process Models. AI generated definition based on: Computer Aided Chemical Engineering, 2018 ...
A Gaussian process (GP) is a collection of random variables with the property that the joint distribution of any finite subset of which is a Gaussian [21]. It generalizes Gaussian distribution to infinitely many random variables and is used as a prior over a latent function. The GP is compl...
关键词: Estimating function Fredholm integral equation Godambe information Intensity function Regression model Spatial point process 年份: 2015 收藏 引用 批量引用 报错 分享 求助全文 通过文献互助平台发起求助,成功后即可免费获取论文全文。 请先登入参考文献 引证文献...
This contribution is devoted to the degeneracy problem occuring when considering the maximum likelihood estimator in the case of multivariate Gaussian mixture modeling. We show that the likeli-hood function is unbounded and we characterize the set of singularity points. We also show that the penalizat...
Interval dataLikelihoodProbability distributionDistribution parametersEpistemic uncertaintyGaussian process interpolationa b s t r a c tThis paper presents a likelihood-based methodology for a probabilistic representation of a stochasticquantity for which only sparse point data and/or interval data may be ...
given a value of θ the probability of observing O is P(O|θ). Thus, a 'natural' estimation process is to choose that value of θ that would maximize the probability that we would actually observe O. In other words, we find the parameter values θ that maximize the following function:...
Then ZðxÞ ¼ max Si maxð0; YiðxÞÞ i is a stationary max-stable process with unit Fre´chet mar- gins. In the Schlather model, YðxÞ is specified as a Gaus- sian process. If the Gaussian random field is isotropic, it has the correlation function qðh; /...
Many statistical models of interest to the natural and social sciences have no tractable likelihood function. Until recently, Bayesian inference for such models was thought in-feasible. Pritchard et al. (1999) intro-duced an algorithm kn... S Barthelmé,N Chopin - International Conference on Mach...
(1984). In addition to the conventional gating logic, it utilized the negative log-likelihood function (goodness of fit or sum of residuals) to further reduce the false track acceptance probability. An analytical technique for the evaluation of the effectiveness of this reduction is presented. The...