Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs
, 2014 In the regression‐discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff.
Sebastian Calonico +2 more
semanticscholar +1 more source
Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models [PDF]
, 2019 Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modelling of complex structural relationships.
Chernozhukov, Victor +4 more
core +3 more sources
Linear programming approach to nonparametric inference under shape restrictions: with an application to regression kink designs [PDF]
arXiv, 2021 We develop a novel method of constructing confidence bands for nonparametric regression functions under shape constraints. This method can be implemented via a linear programming, and it is thus computationally appealing. We illustrate a usage of our proposed method with an application to the regression kink design (RKD).
arxiv
Bootstrap Confidence Interval of Prediction for Small Area Estimation Based on Linear Mixed Model
IOP Conference Series: Earth and Environment, 2018 Linear Mixed Model (LMM) analyzes the relationship between Gaussian response and predictors with either fixed and random effects. Procedures based on LMM have been used to construct estimates of the means of small areas, by exploiting auxiliary ...
F. Novkaniza, K. Notodiputro, B. Sartono
semanticscholar +1 more source
Electronic Journal of Statistics, 2021 Bootstrap for nonparametric regression has been around for more than 30 years. Nevertheless, most results are based on assuming an additive regression model with respect to independent and identical (i.i.d.) errors. An exception is the Local Bootstrap of
Liang Wang, D. Politis
semanticscholar +1 more source
Minimax and Adaptive Inference in Nonparametric Function Estimation [PDF]
Statistical Science 2012, Vol. 27, No. 1, 31-50, 2012 Since Stein's 1956 seminal paper, shrinkage has played a fundamental role in both parametric and nonparametric inference. This article discusses minimaxity and adaptive minimaxity in nonparametric function estimation. Three interrelated problems, function estimation under global integrated squared error, estimation under pointwise squared error, and ...
arxiv +1 more source
Singhing with Confidence: Visualising the Performance of Confidence Structures [PDF]
, 2021 Confidence intervals are an established means of portraying uncertainty about an inferred parameter and can be generated through the use of confidence distributions. For a confidence distribution to be ideal, it must maintain frequentist coverage of the true parameter. This can be represented for a precise distribution by adherence to a cumulative unit
arxiv +1 more source
Median confidence regions in a nonparametric model [PDF]
Electronic Journal of Statistics, 2018 The problem of constructing confidence regions for the median in the nonparametric measurement error model (NMEM) is considered. This problem arises in many settings, including inference about the median lifetime of a complex system arising in ...
Edsel A. Peña, Taeho Kim
semanticscholar +1 more source
Likelihood Ratio as Weight of Forensic Evidence: A Closer Look
, 2017 The forensic science community has increasingly sought quantitative methods for conveying the weight of evidence. Experts from many forensic laboratories summarize their findings in terms of a likelihood ratio.
Iyer, Hari K., Lund, Steven P.
core +1 more source
Nonparametric Density Estimation Using Partially Rank-Ordered Set Samples With Application in Estimating the Distribution of Wheat Yield [PDF]
, 2014 We study nonparametric estimation of an unknown density function $f$ based on the ranked-based observations obtained from a partially rank-ordered set (PROS) sampling design.
Jozani, Mohammad Jafari +2 more
core +1 more source