
Estimating the Copula of a class of TimeChanged Brownian Motions: A nonparametric Approach
Within a highfrequency framework, we propose a nonparametric approach ...
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Robust Estimation in Finite Mixture Models
We observe a nsample, the distribution of which is assumed to belong, o...
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A SieveSMM Estimator for Dynamic Models
This paper proposes a Sieve Simulated Method of Moments (SieveSMM) esti...
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A robust multivariate linear nonparametric maximum likelihood model for ties
Statistical analysis in applied research, across almost every field (e.g...
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NonParametric Inference Adaptive to Intrinsic Dimension
We consider nonparametric estimation and inference of conditional momen...
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Spatial Differencing for Sample Selection Models with Unobserved Heterogeneity
This paper derives identification, estimation, and inference results usi...
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Estimation Of Menarcheal Age Distribution From Imperfectly Recalled Data
In a crosssectional study, pubertal females were asked to recall the ti...
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Estimation of the Number of Components of NonParametric Multivariate Finite Mixture Models
We propose a novel estimator for the number of components (denoted by M) in a Kvariate nonparametric finite mixture model, where the analyst has repeated observations of K≥2 variables that are independent given a finitely supported unobserved variable. Under a mild assumption on the joint distribution of the observed and latent variables, we show that an integral operator T, that is identified from the data, has rank equal to M. Using this observation, and the fact that singular values are stable under perturbations, the estimator of M that we propose is based on a thresholding rule which essentially counts the number of singular values of a consistent estimator of T that are greater than a datadriven threshold. We prove that our estimator of M is consistent, and establish nonasymptotic results which provide finite sample performance guarantees for our estimator. We present a Monte Carlo study which shows that our estimator performs well for samples of moderate size.
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