We adopt a double asymptotic framework where the maximal lag may increase with the sample size. In this paper, we study the Lasso estimator for tting au-toregressive time series models. Popular models for time series of count data are integer-valued autoregressive (INAR) models, for which the literature mainly deals with parametric estimation. In this paper, we study the Lasso estimator for fitting autoregressive time series models. This item may be available elsewhere in EconPapers: Search for items with the same title. The Lasso is a popular model selection and estimation procedure for linear models that enjoys nice theoretical properties. CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): The Lasso is a popular model selection and estimation procedure for linear models that enjoys nice theoretical properties. References: View references in EconPapers View complete reference list from CitEcĬitations: View citations in EconPapers (23) Track citations by RSS feedįull text for ScienceDirect subscribers only A General Autoregressive Model with Markov Switching: Estimation and Consistency Autoregressive Models for Sequences of Graphs Autoregressive Process Modeling Via the Lasso Procedure Neural Network Based Model Predictive Control of Turbulent Gas-Solid Corner Flow Compact Autoregressive Network Arxiv:1909.03830V1 Cs. Panel vector autoregressive (PVAR) models account for interdependencies and het- erogeneities across economies by jointly modeling multiple variables and. Solutions for the Group Lasso were obtained by using the functions of the. Keywords: Autoregressive model Estimation consistency Lasso procedure Model selection Prediction consistency (search for similar items in EconPapers) VAR model which allows to control different dimensions of the sparsity, en. In particular, we derive conditions under which the Lasso estimator for the autoregressive coefficients is model selection consistent, estimation consistent and prediction consistent. The Lasso is a popular model selection and estimation procedure for linear models that enjoys nice theoretical properties. We derive theoretical results establishing various types of consistency. The Lasso is a popular model selection and estimation procedure for linear models that enjoys nice theoretical properties. Journal of Multivariate Analysis, 2011, vol. In this paper, we study the Lasso estimator for tting autoregressive time series models. Autoregressive process modeling via the Lasso procedure The Lasso is a popular model selection and estimation procedure for linear models that enjoys nice theoretical properties.
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