搜索结果: 1-15 共查到“统计学 Likelihood Estimation”相关记录21条 . 查询时间(0.087 秒)
Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions
asymptotic expansion diffusion discrete observation maximum-likelihood estimation transition density
2016/1/25
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions
asymptotic expansion diffusion discrete observation maximum-likelihood estimation transition density
2016/1/20
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
On the Approximate Maximum Likelihood Estimation for Diffusion Processes
Asymptotic expansion Asymptotic normality Consistency Dis- crete time observation Maximum likelihood estimation
2016/1/19
The transition density of a diffusion process does not admit an explicit expression in general, which prevents the full maximum likelihood estimation (MLE) based on discretely observed sample paths. A...
Likelihood Estimation with Incomplete Array Variate Observations
Likelihood Estimation Incomplete Array Variate Observations
2012/11/22
Missing data estimation is an important challenge with high-dimensional data arranged in the form of an array.In this paper we propose a probability model for partially observed multi-way array data. ...
Composite likelihood estimation of sparse Gaussian graphical models with symmetry
Variable selection model selection penalized estimation Gaussian graphical model concentration matrix partial correlation matrix
2012/9/17
In this article, we discuss the composite likelihood estimation of sparse Gaussian graph-ical models. When there are symmetry constraints on the concentration matrix or partial correlation matrix, the...
Nonconcave penalized composite conditional likelihood estimation of sparse Ising models
Composite likelihood coordinatewise optimization Ising model minorization–maximization principle NP-dimension asymptotic theory HIV drug resistance database.
2012/9/17
The Ising model is a useful tool for studying complex interactions within a system. The estimation of such a model, however, is rather challenging, especially in the presence of high-dimensional param...
Maximum Likelihood Estimation of Gaussian Cluster Weighted Models and Relationships with Mixtures of Regression
Cluster-weighted modeling finite mixtures of regression EM-algorithm
2012/9/19
Cluster-weighted modeling (CWM) is a mixture approach for modeling the joint probability of a response variable and a set of explanatory variables. The parame-ters are estimated by means of the expect...
Maximum Likelihood Estimation in Network Models
beta model polytope of degree sequences random graphs Rasch model p1 model
2011/6/20
We study maximum likelihood estimation for the statistical model for both directed and undirected
random graph models in which the degree sequences areminimal sufficient statistics. In the undirected...
Smoothed log-concave maximum likelihood estimation with applications
Classification Functional estimation Log-concave maximum likelihood estimation Log-concavity Smoothing
2011/3/18
We study the smoothed log-concave maximum likelihood estimator of a probability distribution on $\mathbb{R}^d$. This is a fully automatic nonparametric density estimator, obtained as a canonical smoot...
Geometry of maximum likelihood estimation in Gaussian graphical models
Statistics Theory (math.ST) Algebraic Geometry (math.AG) Optimization and Control (math.OC)
2010/12/17
We study maximum likelihood estimation in Gaussian graphical models from a geometric point of view. An algebraic elimination criterion allows us to find exact lower bounds on the number of observation...
Penalized maximum likelihood estimation for generalized linear point processes
Penalized maximum likelihood estimation generalized linear point processes
2010/3/11
A framework of generalized linear point process models (glppm) much akin to glm for regression is developed where the intensity depends upon a linear predictor process through a known function.In the ...
On some problems in the article “Efficient Likelihood Estimation in State Space Models” by Cheng-Der Fuh
problems Efficient Likelihood Estimation State Space Models
2010/3/11
Upon reading the paper Efficient Likelihood Estimation
in State Space Models by Cheng-Der Fuh I found a number of problems in the
formulations and a number of mathematical errors. Together, these fi...
Maximum Lq-likelihood estimation
Maximum Lq-likelihood estimation nonextensive entropy asymptotic efficiency exponential family tail probability estimation
2010/3/10
In this paper, the maximum Lq-likelihood estimator (MLqE), a
new parameter estimator based on nonextensive entropy [Kibernetika
3 (1967) 30–35] is introduced. The properties of the MLqE are stud-
i...
Non-Gaussian Quasi Maximum Likelihood Estimation of GARCH Models
Non-Gaussian Quasi Maximum Likelihood Estimation GARCH Models
2010/3/9
The non-Gaussian quasi maximum likelihood estimator is frequently used
in GARCH models with intension to improve the efficiency of the GARCH
parameters. However, the method is usually inconsistent u...
On approximate pseudo-maximum likelihood estimation for LARCH-processes
asymptotic distribution LARCH process long-range dependence parametricestimation volatility
2010/3/9
Linear ARCH (LARCH) processes were introduced by Robinson [J. Econometrics 47 (1991)
67–84] to model long-range dependence in volatility and leverage. Basic theoretical properties
of LARCH processes...