Zobrazeno 1 - 10
of 122
pro vyhledávání: '"Geyer, Charles J."'
Autor:
Eck, Daniel J., Geyer, Charles J.
In a regular full exponential family, the maximum likelihood estimator (MLE) need not exist in the traditional sense. However, the MLE may exist in the completion of the exponential family. Existing algorithms for finding the MLE in the completion so
Externí odkaz:
http://arxiv.org/abs/1803.11240
We propose a penalized likelihood method that simultaneously fits the multinomial logistic regression model and combines subsets of the response categories. The penalty is non differentiable when pairs of columns in the optimization variable are equa
Externí odkaz:
http://arxiv.org/abs/1705.03594
Precise estimation of expected Darwinian fitness, the expected lifetime number of offspring of organism, is a central component of life history analysis. The aster model serves as a defensible statistical model for distributions of Darwinian fitness.
Externí odkaz:
http://arxiv.org/abs/1701.07910
Publikováno v:
Annals of Applied Statistics 2013, Vol. 7, No. 3, 1778-1795
Random effects are implemented for aster models using two approximations taken from Breslow and Clayton [J. Amer. Statist. Assoc. 88 (1993) 9-25]. Random effects are analytically integrated out of the Laplace approximation to the complete data log li
Externí odkaz:
http://arxiv.org/abs/1311.7482
We propose a penalized likelihood method to jointly estimate multiple precision matrices for use in quadratic discriminant analysis and model based clustering. A ridge penalty and a ridge fusion penalty are used to introduce shrinkage and promote sim
Externí odkaz:
http://arxiv.org/abs/1310.3892
Autor:
Johnson, Leif T., Geyer, Charles J.
Publikováno v:
Annals of Statistics 2012, Vol. 40, No. 6, 3050-3076
A random-walk Metropolis sampler is geometrically ergodic if its equilibrium density is super-exponentially light and satisfies a curvature condition [Stochastic Process. Appl. 85 (2000) 341-361]. Many applications, including Bayesian analysis with c
Externí odkaz:
http://arxiv.org/abs/1302.6741
Autor:
Geyer, Charles J.
If the log likelihood is approximately quadratic with constant Hessian, then the maximum likelihood estimator (MLE) is approximately normally distributed. No other assumptions are required. We do not need independent and identically distributed data.
Externí odkaz:
http://arxiv.org/abs/1206.4762
Autor:
Geyer, Charles J.
When in a full exponential family the maximum likelihood estimate (MLE) does not exist, the MLE may exist in the Barndorff-Nielsen completion of the family. We propose a practical algorithm for finding the MLE in the completion based on repeated line
Externí odkaz:
http://arxiv.org/abs/0901.0455
Autor:
Sung, Yun Ju, Geyer, Charles J.
Publikováno v:
Annals of Statistics 2007, Vol. 35, No. 3, 990-1011
We describe a Monte Carlo method to approximate the maximum likelihood estimate (MLE), when there are missing data and the observed data likelihood is not available in closed form. This method uses simulated missing data that are independent and iden
Externí odkaz:
http://arxiv.org/abs/0708.2184
Publikováno v:
Evolution, 2002 Mar 01. 56(3), 453-463.
Externí odkaz:
https://www.jstor.org/stable/3061585
