Lasso-type problems with adaptive penalties
Adaptive Lasso-type estimation for multivariate diffusion processes
... the LASSO procedure was introduced for linear regression prob- lems, but in recent years this approach has been applied to time series analysis by several authors, mainly in the case of autoregressive ...root ...
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Strong Rules for Discarding Predictors in Lasso-type Problems
... the lasso problem along a sequence of 100 tuning parameter values, equally spaced on the log ...the lasso solution on the x-axis, and the number of predictors left after filtering with the proposed rules ...
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Adaptive Lasso and group-Lasso for functional Poisson regression
... new adaptive Lasso and group-Lasso procedures to estimate the regression function in high dimensional Poisson regression, with a special focus on the calibration of weights involved in the ...the ...
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Self-adaptive penalties in the electromagnetism-like algorithm for constrained global optimization problems
... optimization problems is based on penalty ...unconstrained problems. In this paper, we analyze the implementation of a self-adaptive penalty approach, within the electromagnetism-like ...
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Catching Growth Determinants with the Adaptive LASSO
... The full regressor matrix comprising the constant and all 67 explanatory variables is almost multi-collinear, with a reciprocal condition number of 9.38 × 10 −20 . The full OLS estimator is thus very imprecisely defined ...
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Adaptive-LASSO for Cox's proportional hazards model
... named adaptive-LASSO (ALASSO) ...different penalties for different coefficients: unimportant variables receive larger penalties than important ...
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A sensitivity analysis and error bounds for the adaptive lasso.
... of lasso based on data-driven weights in the penalty term that satisfies de- sired asymptotic properties for high-dimensional problems as suggested by Fan and Li ...of type 1/| ˆ β j | γ ...
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The adaptive Lasso in high dimensional sparse heteroscedastic models
... of problems of this type in the case where the number of parameters in the model varies with the sample ...tive Lasso estimator, which satisfies the oracle property in homoscedastic linear models ...
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Single machine scheduling problems: early-tardy penalties
... this type of performance measures may not interpret the practice and there are many important occasions when non-regular performance measures ...the penalties arise from both early and tardy jobs which ...
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A comparative study of the Lasso-type and heuristic model selection methods
... the Lasso-estimator has some ...the adaptive Lasso (aLasso) (Zou 2006). A special case of the Lasso-type technique with the penalty term’s exponent less than one is analyzed by Knight ...
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Selection and fusion of categorical predictors with L₀-type penalties
... end, Lasso-type penalties on the differences of coefficients are a standard ...the adaptive weights are badly conditioned or not ...to Lasso-type ...
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Comparison of linear regression models Ordinary Lasso, Adaptive Group Lasso and Ordinary Least Squares models in selecting effective characteristics to predict the expected return
... In this study, information sources are divided into two categories; the first one deals with the study of theoretical foundations, research literature, and background research using library resources, internal and ...
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LASSO-Type Penalization in the Framework of Generalized Additive Models for Location, Scale and Shape
... -type penalties, but which extends the previous approaches by including penalization strategies that are specifically designed for nominal or ordinal categorical ...adequate penalties, not only the ...
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Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso
... 1 Introduction Recently there has been a growing literature on the estimation and tests of common breaks in panel data models in which there are individual units and time series observations for each individual. ...
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The Spike-and-Slab LASSO
... Spike-and-Slab LASSO procedure for variable selection and parameter estimation in linear ...non-separable penalties is their ability to borrow strength across coordinates, adapt to en- semble sparsity ...
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Bayesian extensions on Lasso and adaptive Lasso Tobit regressions
... Since lasso method launched, a lot of applications and extensions were run on it which made it to become deeply widely used in various ...Tobit Adaptive Lasso (BTAL) and Bayesian Tobit Lasso ...
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On the distribution of the adaptive LASSO estimator
... the adaptive LASSO estimator is slower than n −1/2 in this ...the adaptive LASSO estimator has been shown in Zou (2006) to possess an ’oracle’ property (under an additional assumption on the ...
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On the distribution of the adaptive LASSO estimator
... We show that the finite-sample as well as the large-sample distributions are typically highly non-normal, regardless of the choice of the tuning pa- rameter. The uniform convergence rate is also obtained, and is shown to ...
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Prediction of Rural Residents’ Consumption Expenditure Based on Lasso and Adaptive Lasso Methods
... the Lasso solu- tion; the entire Lasso solution can be obtained by changing the s values, at this time, this paper uses k -fold CV and Mallows C p criteria to choose the best ...
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The Adaptive Lasso Method for Instrumental Variable Selection.
... 3 Adaptive Lasso with Weak Instruments In Chapter 2, we showed that the limiting distributions of adaptive lasso estimator converge to a degenerate point at 0 when the true coefficient vector ...
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