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Measuring the likelihood of models for network evolution
Measuring the likelihood models network evolution
2013/4/28
Many researchers have hypothesised models which explain the evolution of the topology of a target network. The framework described in this paper gives the likelihood that the target network arose from...
Zero Intelligence Models of the Continuous Double Auction: Empirical Evidence and Generalization
Continuous double auction zero intelligence models econometric estimation consistency asymptotic normality
2013/4/28
The paper is devoted to statistical analysis of zero intelligence models of continuous double auction, in particular to an estimation of parameters of limit order books. We review "classical" zero int...
Criticisms of modelling packet traffic using long-range dependence (extended version)
Criticisms modelling packet traffic long-range dependence
2013/5/2
This paper criticises the notion that long-range dependence is an important contributor to the queuing behaviour of real Internet traffic. The idea is questioned in two different ways. Firstly, a clas...
Simple, asymptotically distribution-free, optimal tests for circular reflective symmetry about a known median direction
Circular statistics Fisher information singularity Rayleigh test for uniformity skewed distributions tests for symmetry
2013/4/28
In this paper, we propose optimal tests for circular reflective symmetry about a fixed median direction. The distributions against which optimality is achieved are the so-called k-sine-skewed distribu...
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...
Surprising Asymptotic Conical Structure in Critical Sample Eigen-Directions
PCA High Dimension Boundary Behavior Consistency
2013/4/28
The aim of this paper is to establish several deep theoretical properties of principal component analysis for multiple-component spike covariance models. Our new results reveal a surprising asymptotic...
Inference about ATE from Observational Studies with Continuous Outcome and Unmeasured Confounding
Inference about ATE Observational Studies Continuous Outcome Unmeasured Confounding
2013/4/28
For settings with a binary treatment and a binary outcome, instrumental variables can be used to construct bounds on a causal treatment effect. With continuous outcomes, meaningful bounds are more dif...
Template matching with noisy patches: A contrast-invariant GLR test
Template matching Likelihood ratio test Detection theory Image restoration
2013/4/28
Matching patches from a noisy image to atoms in a dictionary of patches is a key ingredient to many techniques in image processing and computer vision. By representing with a single atom all patches t...
Template matching with noisy patches: A contrast-invariant GLR test
Template matching Likelihood ratio test Detection theory Image restoration
2013/4/28
Matching patches from a noisy image to atoms in a dictionary of patches is a key ingredient to many techniques in image processing and computer vision. By representing with a single atom all patches t...
A Diffusion Process on Riemannian Manifold for Visual Tracking
racking Particle filtering Template update Generative Template Model Riemannian manifolds log-transformed space.
2013/5/2
Robust visual tracking for long video sequences is a research area that has many important applications. The main challenges include how the target image can be modeled and how this model can be updat...
Volatility Inference in the Presence of Both Endogenous Time and Microstructure Noise
It^o Process Realized Volatility Integrated Volatility Time Endogeneity Market Microstructure Noise
2013/5/2
In this article we consider the volatility inference in the presence of both market microstructure noise and endogenous time. Estimators of the integrated volatility in such a setting are proposed, an...
Network detection is an important capability in many areas of applied research in which data can be represented as a graph of entities and relationships. Oftentimes the object of interest is a relativ...
Sharp Variable Selection of a Sparse Submatrix in a High-Dimensional Noisy Matrix
estimation minimax testing random matrices selection of sparse signal sharp selection bounds variable selection
2013/4/28
We observe a $N\times M$ matrix of independent, identically distributed Gaussian random variables which are centered except for elements of some submatrix of size $n\times m$ where the mean is larger ...
Generalized Measures for the Evaluation of Community Detection Methods
Complex Networks Community Detection Evaluation Measure Cluster Analysis Purity Adjusted Rand Index Normalized Mutual Information
2013/5/2
Community detection can be considered as a variant of cluster analysis applied to complex networks. For this reason, all existing studies have been using tools derived from this field when evaluating ...
Multi-dimensional sparse structured signal approximation using split Bregman iterations
Sparse approximation Regularization Fused-LASSO Split Bregman Multidimensional signals
2013/5/2
The paper focuses on the sparse approximation of signals using overcomplete representations, such that it preserves the (prior) structure of multi-dimensional signals. The underlying optimization prob...