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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Subsampling for Rare Events Data and maximum sampled conditional likelihood
罕见事件数据 子采样 最大采样 条件似然
2023/5/15
In this talk, we show that the available information about unknown parameters in rare events data is only tied to the relatively small number of cases, which justifies the usage of negative sampling. ...
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...
Relaxed Maximum a Posteriori Fault Identification
Fault detection Statistical estimation Convex relaxation Interior-point methods
2015/7/9
We consider the problem of estimating a pattern of faults, represented as a binary vector, from a set of measurements. The measurements can be noise corrupted real values, or quantized versions of noi...
On the Maximum Workload of a Queue Fed by Fractional Brownian Motion
Long-range dependence queues fractional Brownian motion extreme values
2015/7/8
Consider a queue with a stochastic fluid input process modeled as fractional Brownian motion (fBM). When the queue is stable, we prove that the maximum of the workload process observed over an interva...
Relative Performance of Expected and Observed Fisher Information in Covariance Estimation for Maximum Likelihood Estimates
Relative Performance Expected and Observed Fisher Information Covariance Estimation Maximum Likelihood Estimates
2013/6/13
Maximum likelihood estimation is a popular method in statistical inference. As a way of assessing the accuracy of the maximum likelihood estimate (MLE), the calculation of the covariance matrix of the...
Testing Hypotheses by Regularized Maximum Mean Discrepancy
Testing Hypotheses Regularized Maximum Mean Discrepancy
2013/6/14
Do two data samples come from different distributions? Recent studies of this fundamental problem focused on embedding probability distributions into sufficiently rich characteristic Reproducing Kerne...
Hybrid Maximum Likelihood Modulation Classification Using Multiple Radios
Modulation classification data fusion ML esti-mation EM algorithm
2013/4/28
The performance of a modulation classifier is highly sensitive to channel signal-to-noise ratio (SNR). In this paper, we focus on amplitude-phase modulations and propose a modulation classification fr...
Efficient Estimation of Approximate Factor Models via Regularized Maximum Likelihood
High dimensionality unknown factors principal components sparse matrix conditional sparse thresholding cross-sectional correlation penalized maximum likelihood adaptive lasso heteroskedasticity
2012/11/23
We study the estimation of a high dimensional approximate factor model in the presence of both cross sectional dependence and heteroskedasticity. The classical method of principal components analysis ...
The Super Robustness of Maximum Likelihood Location Estimator of Exponential Power Distribution, when p < 1
The Super Robustness Maximum Likelihood Location Estimator Exponential Power Distribution p < 1
2012/9/18
We proof that statistically, the maximum likelihood location estimator of exponential power distribution is strict super robust, when p < 1.
The maximum likelihood drift estimator for mixed fractional Brownian motion
mixed fractional Brownian motion maximum likelihood estimator large sample asymptotic
2012/9/18
The paper is concerned with the maximum likelihood estimator (MLE) of the unknown drift parameterθ∈Rin the continuous-time regression model Xt =θt+Bt +BHt,t ∈[0, T] whereBt is the Brownian motion and ...
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 characterization of distributions
Location parameter Maximum Likelihood Es-timator Minimal necessary sample size MLE characterization Scale pa-rameter Score function.
2012/9/19
Gauss’ principle states that the maximum likelihood estimator of the parameter in a location family is the sample mean for all samples of all sample sizes if and only if the family is Gaussian. There ...
Asymptotic Normality of Maximum Likelihood and its Variational Approximation for Stochastic Blockmodels
network statistics stochastic blockmodeling, varia-tional methods maximum likelihood
2012/9/18
Variational methods for parameter estimation are an activere-search area, potentially offering computationally tractable heuristics with theoretical performance bounds. We build on recent work that ap...