Results 21 to 30 of about 442,883 (292)
Characterization of the asymptotic distribution of semiparametric M-estimators [PDF]
This paper develops a concrete formula for the asymptotic distribution of two-step, possibly non-smooth semiparametric M-estimators under general misspecification.
Ichimura, H, Lee, S
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Parametric and nonparametric inference in equilibrium job search models [PDF]
Equilibrium job search models allow for labor markets with homogeneous workers and firms to yield nondegenerate wage densities. However, the resulting wage densities do not accord well with empirical regularities.
Koop, Gary
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This study used a biresponse nonparametric regression method with truncated spline estimation that used two response variables. Nonparametric regression method is used when the regression curve is not known for its shape and pattern.One of the ...
Ar Ruum Mia Sari +2 more
doaj +1 more source
Bayesian model averaging for nonparametric discontinuity design.
Quasi-experimental research designs, such as regression discontinuity and interrupted time series, allow for causal inference in the absence of a randomized controlled trial, at the cost of additional assumptions.
Max Hinne +3 more
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The nonparametric regression model is applied to regression curves for which the regression curve is unknown. Fourier series estimation is an approach in nonparametric regression, which has high flexibility and is able to adjust to the local nature of ...
Muhammad Danil Pasarella +2 more
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Sparse Nonparametric Graphical Models
Published in at http://dx.doi.org/10.1214/12-STS391 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Lafferty, John +2 more
openaire +4 more sources
Bayesian nonparametric estimation and consistency of mixed multinomial logit choice models [PDF]
This paper develops nonparametric estimation for discrete choice models based on the mixed multinomial logit (MMNL) model. It has been shown that MMNL models encompass all discrete choice models derived under the assumption of random utility maximization,
De Blasi, Pierpaolo +2 more
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Partially fixed bayesian additive regression trees
Bayesian Additive Regression Trees (BART) is a widely popular nonparametric regression model known for its accurate prediction capabilities. In certain situations, there is knowledge suggesting the existence of certain dominant variables.
Hao Ran, Yang Bai
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Semi-parametric regression: Efficiency gains from modeling the nonparametric part
It is widely admitted that structured nonparametric modeling that circumvents the curse of dimensionality is important in nonparametric estimation. In this paper we show that the same holds for semi-parametric estimation.
Mammen, Enno +2 more
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This study presents a comparative analysis of wave buoy analogy models for sea state estimation. A nonparametric, response amplitude operator-based model is introduced as a physics-based approach, while a convolutional neural network is adopted as a ...
Jae-Hoon Lee +2 more
doaj +1 more source

