Provides a random forest based implementation of
the method described in Chapter 7.1.2 (Regression model based anomaly
detection) of Chandola et al. (2009) <doi:10.1145/1541880.1541882>. It
works as follows: Each numeric variable is regressed onto all other
variables by a random forest. If the scaled absolute difference
between observed value and out-of-bag prediction of the corresponding
random forest is suspiciously large, then a value is considered an
outlier. The package offers different options to replace such
outliers, e.g. by realistic values found via predictive mean matching.
Once the method is trained on a reference data, it can be applied to
new data.

Provides a random forest based implementation of the method
described in Chapter 7.1.2 (Regression model based anomaly detection)
of Chandola et al. (2009) <doi:10.1145/1541880.1541882>. It works as
follows: Each numeric variable is regressed onto all other variables
by a random forest. If the scaled absolute difference between observed
value and out-of-bag prediction of the corresponding random forest is
suspiciously large, then a value is considered an outlier. The package
offers different options to replace such outliers, e.g. by realistic
values found via predictive mean matching. Once the method is trained
on a reference data, it can be applied to new data.
ranger, FNN, graphics, stats, missRanger (>= 2.1.0)

outbreaker: Bayesian inference of outbreak dynamics based on
epidemiological and genetic information.
Thibaut Jombart <t.jombart@imperial.ac.uk>, Anne Cori, Xavier
Didelot, Simon Cauchemez, Christophe Fraser, Neil Ferguson
Bayesian inference of outbreak dynamics based on
epidemiological and genetic information.

Bayesian inference of outbreak dynamics based on epidemiological
and genetic information.

Bayesian reconstruction of disease outbreaks by combining
epidemiologic and genomic data
Thibaut Jombart <t.jombart@imperial.ac.uk>, Anne Cori, Xavier Didelot, Simon Cauchemez, Christophe Fraser, Neil Ferguson
Bayesian reconstruction of disease outbreaks using epidemiological and genetic information.