Further, under suitable hypotheses we show that the maximization of the likelihood function of Gaussian cluster weighted models leads to the same parameter estimates of finite mixtures of regression and finite mixtures of regression with concomitant variables. In this sense, the latter ones can be ...
MLE(Maximum likelihood estimation)是一个决定模型参数值的方法。参数值是通过最大化可能性(Maximum likelihood)让整个预测过程能通过我们的模型获得我们正在观察到的数据来得到的(Maximum likelihood estimation is a method that determines values for the parameters of a model. The parameter values are found such ...
下面给出一个估计高斯模型参数的例子: importnumpyasnpimportscipy.optimizeasoptimportscipy.statsasstdefgaussian_Likelihood(log_par,data):N=len(data)mu,sigma=np.exp(log_par)logL=-N*np.log(sigma*np.sqrt(2.0*np.pi))-np.sum(np.power(data-mu,2.)/(2*sigma*sigma))returnlogLdefgaussian_mle(d...
Maximum likelihood esti- mation of parameters in the inverse Gaussian distribution, with un- known origin. Technometrics, 23, 257-263.R. C. H. Cheng and N. Amin. Maximum likelihood estimation of parameters in the Inverse Gaussian distribution, with unknown origin. Technometrics, 23(3):257-264...
翻译总结：理解最大似然估计（Maximum Likelihood Estimation，MLE）这篇文章将讲解如何通过最大似然估计法确定模型参数，并通过实例进行阐述。理解之前，需要对联合概率和事件独立性有一定的基础。在机器学习中，参数定义为模型描述特定现象的关键数值，如随机森林模型中的用户取消订阅预测或线性回归模型中的广告...
(2014). Bayesian and maximum likeli- hood estimation for Gaussian processes on an incomplete lattice. arXiv preprint arXiv:1402.4281.J. R. Stroud, M. L. Stein, and S. Lysen. Bayesian and maximum likelihood estimation for gaussian processes on an incomplete lattice. Journal of Computational ...
Since we are able to write the Gaussian mixture model as a latent-variable model, we can use theEM algorithmto find the maximum likelihood estimators of its parameters. Starting from an initial guess of the parameter vector , the algorithm produces a new estimate of the parameter vector ...
ML estimation of the parameters of a Gaussian mixture More details The following sections contain more details about the theory of maximum likelihood estimation. Estimation of the asymptotic covariance matrix Methods to estimate the asymptotic covariance matrix of maximum likelihood estimators, including OPG...
This paper overviews maximum likelihood and Gaussian methods of estimating continuous time models used in finance. Since the exact likelihood can be constructed only in special cases, much attention has been devoted to the development of methods designed to approximate the likelihood. These approaches ...
This paper describes the maximum-likelihood fitting of a bivariate (more generally, multivariate) Gaussian signal-detection model for rating data. The model applies whenever pairs of detection ratings are recorded under several stimulus conditions. The underlying representation is a bivariate Gaussian distr...