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DOSPortfolio - Dynamic Optimal Shrinkage Portfolio

Constructs dynamic optimal shrinkage estimators for the weights of the global minimum variance portfolio which are reconstructed at given reallocation points as derived in Bodnar, Parolya, and Thorsén (2021) (<arXiv:2106.02131>). Two dynamic shrinkage estimators are available in this package. One using overlapping samples while the other use nonoverlapping samples.

Last updated 3 years ago

4.30 score 4 stars 4 scripts 224 downloads

BayesMultMeta - Bayesian Multivariate Meta-Analysis

Objective Bayesian inference procedures for the parameters of the multivariate random effects model with application to multivariate meta-analysis. The posterior for the model parameters, namely the overall mean vector and the between-study covariance matrix, are assessed by constructing Markov chains based on the Metropolis-Hastings algorithms as developed in Bodnar and Bodnar (2021) (<arXiv:2104.02105>). The Metropolis-Hastings algorithm is designed under the assumption of the normal distribution and the t-distribution when the Berger and Bernardo reference prior and the Jeffreys prior are assigned to the model parameters. Convergence properties of the generated Markov chains are investigated by the rank plots and the split hat-R estimate based on the rank normalization, which are proposed in Vehtari et al. (2021) (<DOI:10.1214/20-BA1221>).

Last updated 2 years ago

1.70 score 212 downloads