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Semiparametric estimation of a sample selection model with a binary endogenous regressor: the effect of chronicity in labour supply
The aim of this paper is to investigate the effect of chronicity in labour supply and the participation equation in a flexible framework. We analyse a semiparametric model for data including problems of sample selection ...
Mixed causal-noncausal autoregressions with exogenous regressors
(Escola de Pós-Graduação em Economia da FGV, 2019-10-09)
The mixed causal-noncausal autoregressive (MAR) model has been proposed to estimate time series processes involving explosive roots in the autoregressive part, as it allows for stationary forward and backward solutions. ...
Seleção de modelos de regressão linear em bases de alta dimensão
(Universidade Federal de Juiz de Fora (UFJF)BrasilICE – Instituto de Ciências ExatasUFJF, 2021)
Functional form estimation using oblique projection matrices for ls-SVM regression models
Kernel regression models have been used as non-parametric methods for fitting experimental data. However, due to their non-parametric nature, they belong to the so-called 'black box' models, indicating that the relation ...
Does the private database help to explain Brazilian inflation?
(2019-01)
The large dimension of variables as regressors requires a reduction in the number of variables, which we do in this paper through the factorial model. This method is useful if the variables are collinear, as is our case. ...
L(1)-regularization of high-dimensional time-series models with non-gaussian and heteroskedastic errors
(Elsevier Science Sa, 2016-03)
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. The adaLASSO is a one-step implementation of the family of folded concave penalized least-squares. ...
Predicción de la demanda de Smartphone de introducción al mercado Colombiano mediante modelos de Machine Learning
(Bogotá D.C : Fundación Universitaria Konrad Lorenz, 2022Escuela de Posgrados, 2022)
El proyecto tiene objetivo pronosticar la cantidad de ventas para productos de introducción al mercado colombiano de equipos celulares. Se entrenaron y validaron distintos modelos de machine learning como lo son: árboles ...
ℓ1-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors
(Elsevier Ltd, 2016)
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. The adaLASSO is a one-step implementation of the family of folded concave penalized least-squares. ...