搜索结果: 1-11 共查到“统计学其他学科 Empirical”相关记录11条 . 查询时间(0.093 秒)
Higher Variations of the Monty Hall Problem (3.0 and 4.0) and Empirical Definition of the Phenomenon of Mathematics, in Boole's Footsteps, as Something the Brain Does
Artificial Intelligence Binary Structure Boolean Algebra Boolean Operators Boole’s Algebra Brain Science, Cognition Cognitive Science Definition of Mathematics Definition of Probability Theory Digital Mathematics Electrical Engineering, Foundations of Mathematics Human Intelligence, Linguistics, Logic, Monty Hall Problem, Neuroscience Non-quantitative and Quantitative Mathematics Probability Theory Rational Thought and Language
2012/9/17
In Advances in Pure Mathematics (www.scirp.org/journal/apm) , Vol. 1, No. 4 (July 2011), pp.
136-154, the mathematical structure of the much discussed problem of probability known as the Monty Ha...
Power-law distributions in binned empirical data
power-law distribution heavy-tailed distributions model selec-tion binned data
2012/9/18
Many man-made and natural phenomena, including the intensity of earthquakes, population of cities, and size of international wars, are believed to follow power-law distributions. The accurate identifi...
Aggregating density estimators: an empirical study
Machine Learning Histogram Kernel Density Estimator Bootstrap,Bagging Boosting, Stacking.
2012/9/19
We present some new density estimation algorithms obtainedby bootstrap ag-gregation like Bagging. Our algorithms are analyzed and empirically compared to other methods found in the statistical literat...
Non-Convex Rank Minimization via an Empirical Bayesian Approach
Non-Convex Rank Minimization via Empirical Bayesian Approach
2012/9/19
In many applications that require matrix solutions of minimal rank, the underlying cost function is non-convex leading to an intractable, NP-hard optimization problem.Consequently, the convex nuclear ...
Regenerative block empirical likelihood for Markov chains
Nummelin splitting technique time series Empirical Likelihood
2011/3/21
Empirical likelihood is a powerful semi-parametric method increasingly investigated in the literature. However, most authors essentially focus on an i.i.d. setting. In the case of dependent data, the ...
The almost sure behavior of certain spatial repartitions of local empirical processes indexed by functions
Empirical process, Functional limit theorems Poisson processes
2011/7/5
We investigate a particular form of weak convergence of the local empirical process.
Decomposition of neuronal assembly activity via empirical de-Poissonization
asymptotics compound Poisson process empirical characteristic function higher-order interactions jump measure
2009/9/16
Consider a compound Poisson process with jump measure $nu$ supported by finitely many positive integers. We propose a method for estimating $nu$ from a single, equidistantly sampled trajectory and dev...
A limited in bandwidth uniformity for the functional limit law of the increments of the empirical process
Empricial processes Functional limit theorems Strong theorems Density estimation LATEX2ε
2009/9/16
Consider the following local empirical process indexed by $K in mathcal{G}$, for fixed $h>0$ and $z in mathbb{R}^d$: $$G_n(K,h,z):=sum_{i=1}^n K (frac{Z_i-z}{h^{1/d}}) - mathbb{E} (K (frac{Z_i-z}{h^{1...
Empirical likelihood based testing for regression
Marked empirical process Model check for regression Nonlinear regression Partial linear model Residuals
2009/9/16
Consider a random vector $(X,Y)$ and let $m(x)=E(Y|X=x)$. We are interested in testing $H_0 : m in {cal M}_{Theta,{cal G}} = {gamma(cdot,theta,g) : theta in Theta, g in {cal G}}$ for some known functi...
One more approach to the convergence of the empirical process to the Brownian bridge
Empirical process Donsker Theorem Brownian bridge
2009/9/16
A theorem of Donsker asserts that the empirical process converges in distribution to the Brownian bridge. The aim of this paper is to provide a new and simple proof of this fact.
Penalized empirical risk minimization over Besov spaces
Penalized empirical risk Besov spaces
2009/9/16
Kernel methods are closely related to the notion of reproducing kernel Hilbert space (RKHS). A kernel machine is based on the minimization of an empirical cost and a stabilizer (usually the norm in th...