搜索结果: 1-15 共查到“统计学 conditional”相关记录46条 . 查询时间(0.099 秒)
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
Closed-form expansion, conditional expectation, and option valuation
asymptotic expansion diffusion option pricing conditional expectation iterated stochastic integral
2016/1/20
Enlightened by the theory of Watanabe [Watanabe S (1987) Analysis of Wiener functionals (Malliavin calculus) and its applications to heat kernels. Ann. Probab. 15:1–39] for analyzing generalized rando...
Conditional limit theorems for critical continous-state branching processes
Empirical likelihood high dimensional data analysis independence sure screening large deviation
2016/1/20
In this paper we study the conditional limit theorems for critical continuous-state branching processes with branching mechanism ψ(λ) = λ 1+α L(1/λ)where α ∈ [0,1] and L is slowly varying at ∞. We pro...
Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions
Conditional characteristic function Diffusion processes Empirical likelihood Kernel smoothing L′ evy driven processes
2016/1/19
Markov processes are used in a wide range of disciplines including finance.The transition densities of these processes are often unknown. However, the conditionalcharacteristic functions are more like...
A Bayesian localised conditional auto-regressive model for estimating the health effects of air pollution
Air pollution and health Conditional autoregressive models Spatial correlation
2013/6/14
Estimation of the long-term health effects of air pollution is a challenging task, especially when modelling small-area disease incidence data in an ecological study design. The challenge comes from t...
Light tails: Gibbs conditional principle under extreme deviation
Light tails Gibbs conditional principle extreme deviation
2013/6/14
Let $X_{1},..,X_{n}$ denote an i.i.d. sample with light tail distribution and $S_{1}^{n}$ denote the sum of its terms; let $a_{n}$ be a real sequence\ going to infinity with $n.$\ In a previous paper ...
Refinement revisited with connections to Bayes error, conditional entropy and calibrated classifiers
Refinement Score Probability Elicitation Calibrated Classifier Bayes Error Bound Conditional Entropy Proper Loss
2013/4/27
The concept of refinement from probability elicitation is considered for proper scoring rules. Taking directions from the axioms of probability, refinement is further clarified using a Hilbert space i...
Efficient Regularized Least-Squares Algorithms for Conditional Ranking on Relational Data
Efficient Regularized;Least-Squares;Algorithms;Conditional Ranking;Relational Data
2012/11/23
In domains like bioinformatics, information retrieval and social network analysis, one can find learning tasks where the goal consists of inferring a ranking of objects, conditioned on a particular ta...
Shrinkage estimators for prediction out-of-sample: Conditional performance
James-Stein estimator rando mmatrix theory random design
2012/11/22
We find that, in a linear model, the James-Stein estimator, which dominates the maximum-likelihood estimator in terms of its in-sample prediction error, can perform poorly compared to the maximum-like...
Conditional simulation of max-stable processes
Conditional simulation Markov chain Monte Carlo Max-stable process Precipitation Regular conditional distribution Temperature.
2012/9/18
Since many environmental processes such as heat waves or precipitation are spatial in extent,it is likely that a single extreme event affects several locations and the areal modelling of ex-tremes is ...
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...
Iterative Conditional Fitting for Gaussian Ancestral Graph Models
Iterative Conditional Fitting Gaussian Ancestral Graph Models
2012/9/19
Ancestral graph models, introduced by Richard-son and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property that is closed under...
Functional kernel estimators of large conditional quantiles
Conditional quantiles heavy-tailed distributions functional kernel estimator
2011/7/19
We address the estimation of conditional quantiles when the covariate is functional and when the order of the quantiles converges to one as the sample size increases.
Loss-sensitive Training of Probabilistic Conditional Random Fields
Loss-sensitive Training Probabilistic Conditional Random Fields
2011/7/19
We consider the problem of training probabilistic conditional random fields (CRFs) in the context of a task where performance is measured using a specific loss function. While maximum likelihood is th...
Uniform bias study and Bahadur representation for local polynomial estimators of the conditional quantile function
Bahadur representation Conditional quantile function Local polynomial estimation Econometrics of Auctions
2011/6/20
This paper investigates the bias and the weak Bahadur representation of a local
polynomial estimator of the conditional quantile function and its derivatives.
The bias and Bahadur remainder term are...