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pro vyhledávání: '"Masini, Ricardo"'
The density weighted average derivative (DWAD) of a regression function is a canonical parameter of interest in economics. Classical first-order large sample distribution theory for kernel-based DWAD estimators relies on tuning parameter restrictions
Externí odkaz:
http://arxiv.org/abs/2301.00277
Yurinskii's coupling is a popular theoretical tool for non-asymptotic distributional analysis in mathematical statistics and applied probability, offering a Gaussian strong approximation with an explicit error bound under easily verifiable conditions
Externí odkaz:
http://arxiv.org/abs/2210.00362
Autor:
Masini, Ricardo
In the context of treatment effect estimation, this paper proposes a new methodology to recover the counterfactual distribution when there is a single (or a few) treated unit and possibly a high-dimensional number of potential controls observed in a
Externí odkaz:
http://arxiv.org/abs/2202.11671
Factor and sparse models are two widely used methods to impose a low-dimensional structure in high-dimensions. However, they are seemingly mutually exclusive. We propose a lifting method that combines the merits of these two models in a supervised le
Externí odkaz:
http://arxiv.org/abs/2102.11341
In this paper we survey the most recent advances in supervised machine learning and high-dimensional models for time series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to penalize
Externí odkaz:
http://arxiv.org/abs/2012.12802
Optimal pricing, i.e., determining the price level that maximizes profit or revenue of a given product, is a vital task for the retail industry. To select such a quantity, one needs first to estimate the price elasticity from the product demand. Regr
Externí odkaz:
http://arxiv.org/abs/2011.03996
Akademický článek
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There has been considerable advance in understanding the properties of sparse regularization procedures in high-dimensional models. In time series context, it is mostly restricted to Gaussian autoregressions or mixing sequences. We study oracle prope
Externí odkaz:
http://arxiv.org/abs/1912.09002
We develop a non-negative polynomial minimum-norm likelihood ratio (PLR) of two distributions of which only moments are known. The sample PLR converges to the unknown population PLR under mild conditions. The methodology allows for additional shape r
Externí odkaz:
http://arxiv.org/abs/1910.14009
Autor:
Masini, Ricardo P.1,2 (AUTHOR), Medeiros, Marcelo C.3 (AUTHOR) mcm@econ.puc-rio.br, Mendes, Eduardo F.4 (AUTHOR)
Publikováno v:
Journal of Economic Surveys. Feb2023, Vol. 37 Issue 1, p76-111. 36p. 6 Diagrams, 1 Chart, 1 Graph.
