Maximum likelihood estimation in a latent variable problem. 1983.Brillinger, D.R. and Preisler, M.K. (1983) Maximum Likelihood Estimation in a Latent Variable Problem. In: Karlin, S., Ameya, T. and Goodman, L.A., Eds., Studies in Econometrics, Time Series and Multivariate Statistics, ...
文献链接:Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift 这篇的作者是Jiawei Ge, Shange Tang, Jianqing Fan, Cong Ma, Chi Jin, 也是迁移学习的工作, 就在一个月前放上arxiv. 这题目很有趣,MLE is all you need.这个Note作得也比较草率... ...
a MLE can be obtained as a solution to the following problem; max θ∈Θ log (y; θ) = max θ∈Θ L(y; θ) Proposition 2 (Sufficient condition for existence) If the parameter space Θ is compact and if the likelihood function θ → (y; θ) is continuous on Θ, then there ex...
最大似然估计 An Introductory Guide to Maximum Likelihood Estimation (with a case study in R) 最大似然估计就是已知数据来求模型的最适参数,maximize the probability of observing the data。 Given the observed data and a model of interest, we need to find the one Probability Density Function/Probabi...
Maximum likelihood (ML) estimation is a popular approach in solving many signal processing problems. Many of these problems cannot be solved analytically and so numerical techniques such as the method of scoring are applied. However, in many scenarios, it is desirable to modify the ML problem wit...
The Poisson quasi-maximum likelihood estimator: A solution to the "adding up" problem in gravity models 来自 EconPapers 喜欢 0 阅读量: 75 作者: Jean-Francis Arvis,Ben Shepherd 摘要: This article shows that the Poisson Quasi-Maximum Likelihood (QML) estimator applied to the gravity model ...
3.2. the maximum likelihood 3.3. lmom 4. Discussion: 4.1. the nls 1.1 singular gradient problem As I already the estimation of my three parameters, so I use them as the guess, then there is no singular gradient error again 1.2 The parameters are slight different from the results got from...
The concept of maximum likelihood estimation is a general and ubiquitous one in statistics and refers to a procedure whereby the parameters of a model are optimized by maximizing the joint probability or probability density of observed measurements based on an assumed distribution of those measurements...
As a consequence, an empirical best linear unbiased predictor of a small area mean, commonly used in small area estimation, could reduce to a simple regression estimator, which typically has an overshrinking problem. We propose an adjusted maximum likelihood estimator of the model variance that ...
Maximum Likelihood Estimation of the Number of True Null Hypotheses in a Multiple Testing Problem 来自 ResearchGate 喜欢 0 阅读量: 32 作者: HM Hsueh 摘要: When there are many hypotheses to be tested, the risk of a false positive finding in the simultaneous inference increases severely. A ...