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From Sparse Signals to Sparse Residuals for Robust Sensing
Sparse Signals Sparse Residuals
2010/11/8
One of the key challenges in sensor networks is the extraction of information by fusing data from a multitude of distinct, but possibly unreliable sensors. Recovering information from the maximum numb...
Semi-parametric dynamic time series modelling with applications to detecting neural dynamics
Dynamic time series modeling change-point testing Bayesian statistics statistics for neural data
2010/11/8
This paper illustrates novel methods for nonstationary time se-ries modeling along with their applications to selected problems in neuroscience. These methods are semi-parametric in that inferences ar...
Bayesian inference and model choice in a hidden stochastic two-compartment model of hematopoietic stem cell fate decisions
Stochastic two-compartment model hidden Markov models reversible jump MCMC hematopoiesis stem cell asymmetric division
2010/11/8
Despite rapid advances in experimental cell biology, the in vivo behavior of hematopoietic stem cells (HSC) cannot be directly ob-served and measured. Previously we modeled feline hematopoiesis using ...
A Conversation with James Hannan
Hannan consistency repeated games compound decision theory empirical Bayes
2010/11/9
Jim Hannan is a professor who has lived an interesting life and one whose fundamental research in repeated games was not fully appreciated until late in his career. During his service as a meteorologi...
Perturbation of matrices and non-negative rank with a view toward statistical models
Euclidean topology Jacobian matrix mixture models
2010/10/19
In this paper we study how perturbing a matrix changes its non-negative rank. We show that the non-negative rank is upper-semicontinuos and we describe some special families of perturbations. We apply...
A statistical framework is introduced for a broad class of problems involving synchronization or registration of data across a sensor network in the presence of noise. This framework enables an estim...
Predicting Inflation: Professional Experts Versus No-Change Forecasts
inflation predictive distribution reference forecast
2010/10/19
We compare forecasts of United States inflation from the Survey of Professional Forecasters (SPF) to predictions made by simple statistical techniques. In nowcasting, economic expertise is persuasive...
Closed-form cdf and pdf of Tukey's h-distribution, the heavy-tail Lambert W approach, and how to bijectively "Gaussianize" heavy-tailed data
family of heavy-tailed distributions Tukey g-h distribution Lambert W
2010/10/19
Recently Goerg (2010) introduced Lambert W - F random variables (RVs), a new family of generalized skewed distributions. Here I will adapt this appealing framework to generate heavy (heavier) tailed ...
Testing Parallelism of Nonparametric Regression Curves
Testing Parallelism Nonparametric Regression Curves
2010/10/19
This paper considers the inference of regression functions in the context of multiple time series. For an arbitrary number of time series observed at a large number of time points, we test the hypoth...
Hidden Markov models for alcoholism treatment trial data
Hidden Markov models alcoholism clinical trial
2010/10/19
In a clinical trial of a treatment for alcoholism, a common response variable of interest is the number of alcoholic drinks consumed by each subject each day, or an ordinal version of this response, ...
An MDL approach to the climate segmentation problem
Changepoints genetic algorithm level shifts
2010/10/19
This paper proposes an information theory approach to estimate the number of changepoints and their locations in a climatic time series. A model is introduced that has an unknown number of changepoint...
We consider heteroscedastic nonparametric regression models, when both the mean function and variance function are unknown and to be estimated with nonparametric approaches. We derive convergence rate...
Approximation of conditional densities by smooth mixtures of regressions
Finite mixtures of normal distributions smoothly mixing regressions mixtures of experts Bayesian conditional density estimation
2010/10/14
This paper shows that large nonparametric classes of conditional multivariate densities can be approximated in the Kullback--Leibler distance by different specifications of finite mixtures of normal ...
Inference and Modeling with Log-concave Distributions
Nonparametric density estimation shape constraint log-concave density Polya frequency function
2010/10/14
Log-concave distributions are an attractive choice for modeling and inference, for several reasons: The class of log-concave distributions contains most of the commonly used parametric distributions ...
加强乡镇统计工作是提高统计数据质量的固本之策
乡镇统计工作 统计数据质量 固本之策
2009/9/7
数据质量是统计工作的生命。只有源头数据准确可靠，才能有统计数据的高质量；只有坚实的乡镇（街道办事处）统计工作，才能保证源头统计数据的真实可信。然而，乡镇（街道办事处）的统计工作现状如何？源头数据质量又怎样呢？笔者通过调查发现，乡镇（街道办事处）统计机构建设与当前肩负的统计工作任务不相适应，人员素质与质量要求有差距，基层统计工作呼唤统计机构亟待加强。