Main objective of a predictive model is to provide accurated predictions of a new observations.
Unfortunately we don't know how well the model performs. In addition, at the current era of omic
data where p >> n, is not reasonable applying internal validation using data-splitting. Under this
background a good method to assessing model performance is applying internal bootstrap validation
(Harrell Jr, Frank E (2015) <doi:10.1007/978-1-4757-3462-1>.) This package provides bootstrap validation
for the linear, logistic, multinomial and cox 'glmnet' models.
glmnet, pbapply, pROC, parallel, survival, risksetROC

Main objective of a predictive model is to provide accurated predictions of a new observations.
Unfortunately we don't know how well the model performs. In addition, at the current era of omic
data where p >> n, is not reasonable applying internal validation using data-splitting. Under this
background a good method to assessing model performance is applying internal bootstrap validation
(Harrell Jr, Frank E (2015) <doi:10.1007/978-1-4757-3462-1>.) This package provides bootstrap validation
for the linear, logistic, multinomial and cox 'glmnet' models as well as lm and glm models.

Test Stationarity using Bootstrap Wavelet Packet Tests
c(person("Guy", "Nason", role=c("aut", "cre"),
email="g.nason@imperial.ac.uk"),
person("Alessandro", "Cardinali", role=c("aut"),
email="alessandro.cardinali@plymouth.ac.uk"))
Provides significance tests for second-order stationarity
for time series using bootstrap wavelet packet tests.
Provides functionality to visualize the time series with
the results of the hypothesis tests superimposed.
The methodology is described in Cardinali, A and Nason, G P (2016)
"Practical powerful wavelet packet tests for second-order stationarity."
Applied and Computational Harmonic Analysis, 44, 558-585
<doi:10.1016/j.acha.2016.06.006>.
Guy Nason [aut, cre],
Alessandro Cardinali [aut]

c(person("Guy", "Nason", role=c("aut", "cre"),
email="g.p.nason@bristol.ac.uk"),
person("Alessandro", "Cardinali", role=c("aut"),
email="alessandro.cardinali@plymouth.ac.uk"))
Provides significance tests for second-order stationarity
for time series using bootstrap wavelet packet tests.