Title: Bootstrap Prediction Intervals and Bias-Corrected Forecasting
Maintainer: Jae H. Kim <Jae.Kim@BusEco.monash.edu.au>
Description: Bias-Corrected Forecasting and Bootstrap Prediction Intervals for Autoregressive Time Series
Packaged: Sun Apr 20 12:37:17 2008; jaekim

Packaged: Thu Jun 12 00:01:38 2008; jaekim

Description: Bias-Corrected Forecasting and Bootstrap Prediction
Intervals for Autoregressive Time Series

Maintainer: Jae H. Kim <J.Kim@latrobe.edu.au>

Author: Jae. H. Kim <jaekim8080@gmail.com>
Maintainer: Jae H. Kim <jaekim8080@gmail.com>
Description: Contains functions for bias-Corrected Forecasting and Bootstrap Prediction Intervals for Autoregressive Time Series.

Title: Adjusting for Optimism in 'glmnet' Regression using
Maintainer: Antonio Jose Canada Martinez <ancamar2@gmail.com>
Description: 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 and logistic 'glmnet' models.
Imports: glmnet, pbapply, pROC, parallel

for the linear, logistic, multinomial and cox 'glmnet' models.
Imports: glmnet, pbapply, pROC, parallel, survival, risksetROC

for the linear, logistic, multinomial and cox 'glmnet' models as well as lm and glm models.

Title: Test Stationarity using Bootstrap Wavelet Packet Tests
Authors@R: c(person("Guy", "Nason", role=c("aut", "cre"),
Depends: R (>= 2.0), wavethresh, tseries
Description: 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