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stsc() function.stsc and dsc
objects: summary.stsc_obj and summary.dsc_obj
for generating plots showing the evolution of the tuning parameter, as
well as standard accuracy metrics such as Mean-Squared-Error,
Continuous-Ranked-Probability-Score, and
Predictive-Log-Likelihood-Score.bias for
stsc() and tvc, allowing users to decide
whether bias correction should be applied to the F-Signals in the
TVC-models.incl for
stsc() and dsc, enabling users to specify
whether certain signals are required to be included in the subsets.dsc().burn_in_tvc to
burn_in and sample_length to
init.risk_aversion,
min_weight, and max_weight into
portfolio_arguments.stsc() method.delta in the second step of the
stsc() method now already applies to the most recent
predictive likelihood score in t-1, as stated in Equation (13) in
Adaemmer et al. (2023). Previously, the score in t-1 was given a weight
of 1.0stsc() to decide whether the
subset combinations in the second step of the method should be combined
with equal weights (as proposed in Adaemmer et al. (2023)) or with
weights derived from the predictive log-likelihood scores.stsc() to directly apply the
STSC-algorithm from Adaemmer, Lehmann and Schuessler (2023). This
function is faster and more memory efficient than subsequently applying
tvc() and dsc() as it is now completely
written in Rcpp.NEWS.md file to track changes to the
package.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.