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- W4317209346 abstract "In this paper we introduce a new methodology to determine an optimal coefficient of penalized functional regression. We assume the dependent, independent variables and the regression coefficients are functions of time and error dynamics follow a stochastic differential equation. First we construct our objective function as a time dependent residual sum of square and then minimize it with respect to regression coefficients subject to different error dynamics such as LASSO, group LASSO, fused LASSO and cubic smoothing spline. Then we use Feynman-type path integral approach to determine a Schrodinger-type equation which have the entire information of the system. Using first order conditions with respect to these coefficients give us a closed form solution of them." @default.
- W4317209346 created "2023-01-18" @default.
- W4317209346 creator A5061967156 @default.
- W4317209346 creator A5066586965 @default.
- W4317209346 date "2021-07-05" @default.
- W4317209346 modified "2023-10-16" @default.
- W4317209346 title "Optimal Estimation of Brownian Penalized Regression Coefficients" @default.
- W4317209346 doi "https://doi.org/10.48550/arxiv.2107.02291" @default.
- W4317209346 hasPublicationYear "2021" @default.
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