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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...
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...
Statistical inference for discrete-time samples from affine stochastic delay differential equations
asymptotic normality composite likelihood consistency discrete time observation of continuous-time models prediction-based estimating functions pseudo-likelihood stochastic delay differential equation
2013/4/28
Statistical inference for discrete time observations of an affine stochastic delay differential equation is considered. The main focus is on maximum pseudo-likelihood estimators, which are easy to cal...
Generalized Thompson Sampling for Sequential Decision-Making and Causal Inference
Generalized Thompson Sampling Sequential Decision-Making Causal Inference
2013/5/2
Recently, it has been shown how sampling actions from the predictive distribution over the optimal action-sometimes called Thompson sampling-can be applied to solve sequential adaptive control problem...
The linear stochastic order and directed inference for multivariate ordered distributions
Nonparametric tests order-restricted statistical inference stochastic order relations
2013/4/27
Researchers are often interested in drawing inferences regarding the order between two experimental groups on the basis of multivariate response data. Since standard multivariate methods are designed ...
A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation
A Fast Iterative Bayesian Inference Algorithm Sparse Channel Estimation
2013/4/27
In this paper, we present a Bayesian channel estimation algorithm for multicarrier receivers based on pilot symbol observations. The inherent sparse nature of wireless multipath channels is exploited ...
Variational Inference in Nonconjugate Models
Variational inference Nonconjugat emodels Laplace approximations The delta method
2012/11/22
Mean-field variational inference is widely used for approximate posterior inference in many probabilistic models. When the model is conditionally conjugate, variational updates are in closed-form. How...
On nonparametric inference for $P(Xired variables
nonparametric inference $P(X paired variables
2012/11/22
We propose a class of nonparametric point estimators for $\theta=P(Xere $(X,Y)$ are paired, possibly dependent, continuous random variables. We make use of the pairing structure fo...
Statistical inference in compound functional models
Compound functional model minimax estimation sparse additive structure dimen-sion reduction structure adaptation
2012/9/18
We consider a general nonparametric regression model called the compound model. It includes,as special cases, sparse additive regression and nonparametric (or linear) regression with many covariates b...
Geometry of faithfulness assumption in causal inference
causal inference PC-algorithm (strong) faithfulness conditional independence directed acyclic graph structural equation model real algebraic hypersurface Crofton's formula algebraic statistics.
2012/9/18
Many algorithms for inferring causality rely heavily on the faithfulness assumption.The main justi cation for imposing this assumption is that the set of unfaithful distribu-tions has Lebesgue measure...
Statistical Inference of Allopolyploid Species Networks in the Presence of Incomplete Lineage Sorting
Allopolyploid hybridization Bayesian phylogenetics network
2012/9/18
Polyploidy is an important speciation mechanism, particularly in land plants. Allopolyploid species are formed after hybridization betweenother-wise intersterile parental species. Recent theoretical p...
Nonparametric Inference for Max-Stable Dependence
Nonparametric Inference Max-Stable Dependence
2012/9/17
The choice for parametric techniques in the dis-cussion article is motivated by the claim that for multivariate extreme-value distributions, “owing to
the curse of dimensionality, nonparametric estim...
Inference of time-varying regression models
Information criterion locally stationary processes nonpara-metric hypothesis testings time-varying coefficient models variable selection.
2012/9/17
We consider parameter estimation, hypothesis testing and vari-able selection for partially time-varying coefficient models. Our asymp-totic theory has the useful feature that it can allow dependent, n...
Bayesian inference on dependence in multivariate longitudinal data
Cholesky decomposition covariance matrix moment-matching oxidative stress random effects shrinkage prior.
2012/9/17
In many applications, it is of interest to assess the dependence structure in multivariate longitudinal data. Discovering such dependence is challenging
due to the dimensionality involved. By concate...
Massive parallelization of serial inference algorithms for a complex generalized linear model
Massive parallelization serial inference algorithms generalized linear model
2012/9/17
Following a series of high-pro le drug safety disasters in recent years, many countries are redoubling their e orts to ensure the safety of licensed medical products. Large-scale observa-tional databa...