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Shuffle of min’s random variable approximations of bivariate copulas’realization
Copula Shuffle of Min approximation Narrow bounds of copula
2016/1/26
The comonotonicity and countermonotonicity provide intuitive upper and lower depen-dence relationship between random variables. This paper constructs the shuffle of min’s ran-domvariableapproximations...
The Voter Model in a Random Environment in Z^d
voter model random walk random environment duality
2016/1/25
We consider the voter model with flip rates determined by(μ e ,e ∈ E d ), where E d is the set of all non-oriented nearest-neighbour edges in the Euclidean lattice Z d . Suppose that (μ e ,e ∈ E d ) a...
HodgeRank on Random Graphs for Subjective Video Quality Assessment
Video Quality Assessment Paired Comparison HodgeRank Random Graphs Persistence Homology
2016/1/25
This paper introduces a novel framework, HodgeR-ank on Random Graphs (HRRG), based on paired comparison,for subjective video quality assessment. Two types of random graph models are studied, i.e., Erd...
Shuffle of min’s random variable approximations of bivariate copulas’realization
random variable approximations bivariate copulas realization
2016/1/20
The comonotonicity and countermonotonicity provide intuitive upper and lower depen-dence relationship between random variables. This paper constructs the shuffle of min’s ran-domvariableapproximations...
HodgeRank on Random Graphs for Subjective Video Quality Assessment
Video Quality Assessment Paired Comparison HodgeRank Random Graphs Persistence Homology
2016/1/20
This paper introduces a novel framework, HodgeR-ank on Random Graphs (HRRG), based on paired comparison,for subjective video quality assessment. Two types of random graph models are studied, i.e., Erd...
Spatial Panels: Random Components vs. Fixed Effects
Random components Fixed e¤ects Maximum likelihood estimation Pooling
2016/1/19
This paper investigates spatial panel data models with a space-time …lter in disturbances. We consider their estimation by both …xed e¤ects and random e¤ects speci…cations. With a between equation pro...
Saddlepoint Approximation for Moments of Random Variables
Saddlepoint Approximation Higher moments Sums of i.i.d.ran- dom variables
2016/1/19
In this paper we introduce a saddlepoint approximation method for higher-order moments like E(S − a) m+ ,a > 0, where the random variable S in these expectations could be a single random variabl...
Confidence Intervals for Random Forests:The Jackknife and the Infinitesimal Jackknife
bagging jackknife methods Monte Carlo noise variance estimation
2015/8/21
We study the variability of predictions made by bagged learners and random forests, and show how to estimate standard errors for these methods. Our work builds on variance estimates for bagging propos...
Efficient Prediction Designs for Random Fields
optimal design pareto front empirical kriging gaussian process models
2013/6/14
For estimation and predictions of random fields it is increasingly acknowledged that the kriging variance may be a poor representative of true uncertainty. Experimental designs based on more elaborate...
A limit theorem for scaled eigenvectors of random dot product graphs
limit theorem scaled eigenvectors random dot product graphs
2013/6/14
We prove a central limit theorem for the components of the largest eigenvector of the adjacency matrix of a one-dimensional random dot product graph whose true latent positions are unknown. In particu...
Comparing composite likelihood methods based on pairs for spatial Gaussian random fieldsM
Covariance estimation Geostatistics Large datasets Tapering
2013/6/14
In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators have nice features when...
Random Latin squares and Sudoku designs generation
Random Latin squares and Sudoku designs generation
2013/6/14
Uniform random generation of Latin squares is a classical problem. In this paper we prove that both Latin squares and Sudoku designs are maximum cliques of properly defined graphs. We have developed a...
Inferring Team Strengths Using a Discrete Markov Random Field
Inferring Team Strengths Discrete Markov Random Field
2013/6/14
We propose an original model for inferring team strengths using a Markov Random Field, which can be used to generate historical estimates of the offensive and defensive strengths of a team over time. ...
CLT for linear spectral statistics of random matrix $S^{-1}T$
CLT linear spectral statistics random matrix $S^{-1}T$
2013/6/13
This paper proposes a CLT for linear spectral statistics of random matrix $S^{-1}T$ for a general non-negative definite and {\bf non-random} Hermitian matrix $T$.
Random generation of optimal saturated designs
Design of experiments Optimal designs Unobserved species Discovery probability
2013/4/28
Efficient algorithms for searching for optimal saturated designs are widely available. They maximize a given efficiency measure (such as D-optimality) and provide an optimum design. Nevertheless, they...