shrinkage to target methods for the sample covariance matrix. Alternatively, the identity matrix, a single factor model, and … equicorrelation are used as targets. Since the shrinkage intensity decreases towards zero with increasing sample size, the estimator …

’s natural shrinkage caused by the removal of the dead cells’ mortal remains. The significance of this phenomenon for the … tumour expansion and shrinkage and another improving the performance of the chain shifting approach. Simulations are …

, we suggest using the matrix obtained from the sample covariance matrix through a transformation called shrinkage. This … where it matters most. Statistically, the challenge is to know the optimal shrinkage intensity, and we give the formula for … shrinkage reduces tracking error relative to a benchmark index, and substantially increases the realized information ratio of …

these models. We implement a Bayesian shrinkage combination methodology to include information that is not captured by the …, these results outperform shrinkage forecasts that consider other priors as equal or zero weights. …

. Indeed, this enforces a form of shrinkage on the weights which ensures good out-of-sample performance of the combined …

their theoretical properties. An important property known to hold in these models is selective shrinkage: a unique property …-component prior. An immediate consequence is that a strong selective shrinkage property holds. Interestingly, the conditions needed …

This paper examines the properties of Bayes shrinkage estimators for dynamic regressions that are based on hierarchical … versions of the typical normal prior. Various popular penalized least squares estimators for shrinkage and selection in … for the period 1959–2010, I extensively evaluate the forecasting properties of Bayesian shrinkage in macroeconomic …

This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarchical Normal …-Gamma priors. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered … – 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results …