搜索结果: 1-13 共查到“数理统计学 applications”相关记录13条 . 查询时间(0.078 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Causal Inference based models and their applications in Banking
因果推理 模型 银行业
2023/11/29
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Statistical Management Theory for Business Applications with Massive Scale
大规模 商业应用 统计管理
2023/12/11
The 4th International Workshop on Statistical Modeling of Heavy-Tail Phenomena with Applications
The 4th International Workshop Statistical Modeling of Heavy-Tail Phenomena with Applications
2017/12/20
Heavy-tailed distribution theory, alongside with extreme value theory, provide a framework and an indispensable set of tools aiming to analyze the data's atypical behaviors. The eld is driven by and ...
Varying Naive Bayes Models with Applications toClassi cation of Chinese Text Documents
BIC Chinese Document Classification Screening Consistency
2016/1/25
Document classification is an area of great importance for which many clas-sification methods have been well developed. However, most of these methods cannot generate time-dependent classification rul...
We use Klee’s Dehn-Sommerville relations and other results on face numbers of homology manifolds without boundary to (i) prove Kalai’s conjecture providing lower bounds on the f-vectors of an even-dim...
Applications of the lasso and grouped lasso to the estimation of sparse graphical models
lasso and grouped lasso sparse graphical models
2015/8/21
We propose several methods for estimating edge-sparse and nodesparse graphical models based on lasso and grouped lasso penalties.We develop efficient algorithms for fitting these models when the numbe...
Extremal Distribution for the Discrete 5-convex Stochastic Ordering and Applications
s-convex order moment space extremal distribution branching process Lundberg's coeffici
2011/11/9
In this paper, motivated by the idea from Courtois and Denuit et al.(2006), we derive extremal distribution for the discrete 5-convex stochastic ordering. As applications,We improve lower and upper bo...
A simple variance inequality for U-statistics of a Markov chain with applications
U-statistics Markov chains Inequalities Limit theorems Law of large numbers
2011/9/5
Abstract: We establish a simple variance inequality for U-statistics whose underlying sequence of random variables is an ergodic Markov Chain. The constants in this inequality are explicit and depend ...
Expectiles for subordinated Gaussian processes with applications
expectiles robustness local shift sensitivity subordinated Gaussian process fractional Brownian motion
2011/8/24
Abstract: In this paper, we introduce a new class of estimators of the Hurst exponent of the fractional Brownian motion (fBm) process. These estimators are based on sample expectiles of discrete varia...
Approximate group context tree: applications to dynamic programming and dynamic choice models
categorical time series group context tree dynamic discrete choice models dynamic programming model selection VLMC
2011/9/29
Abstract: The paper considers a variable length Markov chain model associated with a group of stationary processes that share the same context tree but potentially different conditional probabilities....
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Inverse Power Method Nonlinear Eigenproblems
2011/1/4
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors amounts to finding cri...
Approximate tail probabilities of the maximum of a chi-square field on multi-dimensional lattice points and their applications to detection of loci interactions
Approximate tail probabilities a chi-square field multi-dimensional lattice points
2011/1/4
Define a chi-square random field on a multi-dimensional lattice points index set with a direct-product covariance structure, and consider the distribution of the maximum of this random field. We provi...
Dynamic interactions in terms of senders, hubs, and receivers (SHR) using the singular value decomposition of time series: Theory and brain connectivity applications
Dynamic interactions senders hubs receivers singular value decomposition of time series: Theory and brain connectivity applications
2010/12/15
Understanding of normal and pathological brain function requires the identification and localization of functional connections between specialized regions. The availability of high time resolution sig...