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Testing Additive Separability of Error Term in Nonparametric Structural Models
Additive Separability Hypotheses Testing Nonparametric Structural Equation Non- separable Models
2016/1/25
This paper considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model non-additively.We...
Testing Additive Separability of Error Term in Nonparametric Structural Models
Additive Separability Hypotheses Testing Nonparametric Structural Equation
2016/1/20
This paper considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model non-additively.We...
On l2 Error Bounds of the Elastic Net when p>>n
Lasso naive Elastic Net Elastic Net model selection consistency estimation consistency
2016/1/20
We study the estimation property of the Elastic Net in high-dimensional settings where the number of parameters p is comparable to or larger than the sample size n. In such a situation one often assum...
Accounting for Expectational and Structural Error in Binary Choice Problems: A Moment Inequality Approach
discrete choice models moment inequalities entry models
2015/7/17
Many economic decisions involve a binary choice - for example, when consumers decide to purchase a good or when rms decide to enter a new market.
In such settings, agents' choices often depend on im...
On Achieving Reduced Error Propagation Sensitivity in DFE Design via Convex Optimization
On Achieving Reduced Propagation Sensitivity DFE Design via Convex Optimization
2015/7/10
Decision Feedback Equalization (DFE) is expected in digital TV receivers and other high error rate environments. Error propagation usually occurs in infrequent bursts. It is argued here that the minim...
Coverage Error for Confidence Intervals Arising in Simulation Output Analysis
Coverage Error Confidence Intervals Arising Simulation Output Analysis
2015/7/8
Coverage error asymptotics for confidence intervals arising in simulation are discussed~ Asymptotic expansions, to order O(n-1) (n is the sample size), are given for confidence intervals associated wi...
Discretization Error in Simulation of One-dimensional Reflecting Brownian Motion
Discretization Error Simulation One-dimensional Reflecting Brownian Motion
2015/7/8
This paper is concerned with various aspects of the simulation of one-dimensional reflected (or regulated) Brownian motion. The main result shows that the discretization error associated with the Eule...
On the Marginal Standard Error Rule and the Testing of Initial Transient Deletion Methods
Marginal Standard Error Rule Testing Initial Transient Deletion Methods
2015/7/6
In this paper, we introduce several theoretically useful measures for the magni- tude of the initial transient in the setting of single replication steady-state simulations. These measures help suppor...
ERROR ANALYSIS OF COARSE-GRAINED KINETIC MONTE CARLO METHOD
Coarse grain kinetic monte carlo simulation grid the stochastic dynamics structural model
2014/12/25
In this paper we investigate the approximation properties of the coarse-graining procedure applied to kinetic Monte Carlo simulations of lattice stochastic dynamics. We provide both analytical and num...
Noisy Laplace deconvolution with error in the operator
Laplace convolution blind deconvolution nonparametric adaptive estima-tion linear inverse problems error in the operator
2013/4/28
We adress the problem of Laplace deconvolution with random noise in a regression framework. The time set is not considered to be fixed, but grows with the number of observation points. Moreover, the c...
Goal-oriented error estimation for reduced basis method, with application to certified sensitivity analysis
reduced basis method surrogate model reduced order modelling re-sponse surface method scientific computation sensitivity analysis Sobol index computation Monte-Carlo method
2013/5/2
The reduced basis method is a powerful model reduction technique designed to speed up the computation of multiple numerical solutions of parameterized partial differential equations (PDEs). We conside...
Asymptotic Normality of Estimates in Flexible Seasonal Time Series Model with Weak Dependent Error Terms
seasonal time series model local linear estimates consistency and asymptotic
2013/5/2
In this paper we considered a general seasonal time series model with K-dependent and \rambda-dependent errors, which are new concepts of dependence. In this model we derived consistency and asymptoti...
Refinement revisited with connections to Bayes error, conditional entropy and calibrated classifiers
Refinement Score Probability Elicitation Calibrated Classifier Bayes Error Bound Conditional Entropy Proper Loss
2013/4/27
The concept of refinement from probability elicitation is considered for proper scoring rules. Taking directions from the axioms of probability, refinement is further clarified using a Hilbert space i...
Adaptive quantile estimation in deconvolution with unknown error distribution
Deconvolution Quantile and distribution function Adaptive es-timation Minimax convergence rates Random Fourier multiplier
2013/4/27
We study the problem of quantile estimation in deconvolution with ordinary smooth error distributions. In particular, we focus on the more realistic setup of unknown error distributions. We develop a ...
The Future Has Thicker Tails than the Past: Model Error As Branching Counterfactuals
Fukushima Counterfactual histories Risk management Epistemology of probability Model errors Fragility and Antifragility Fourth Quadrant
2012/11/23
Ex ante forecast outcomes should be interpreted as counterfactuals (potential histories), with errors as the spread between outcomes. Reapplying measurements of uncertainty about the estimation errors...