exuber v0.3.0

0

Monthly downloads

0th

Percentile

Econometric Analysis of Explosive Time Series

Testing for and dating periods of explosive dynamics (exuberance) in time series using the univariate and panel recursive unit root tests proposed by Phillips et al. (2015) <doi:10.1111/iere.12132> and Pavlidis et al. (2016) <doi:10.1007/s11146-015-9531-2>. The recursive least-squares algorithm utilizes the matrix inversion lemma to avoid matrix inversion which results in significant speed improvements. Simulation of a variety of periodically-collapsing bubble processes.

Readme

exuber

CRAN\_Status\_Badge Project Status: Active – The project has reached a stable, usable
state and is being actively
developed. lifecycle Build
Status AppVeyor Build
Status codecov

Testing for and dating periods of explosive dynamics (exuberance) in time series using the univariate and panel recursive unit root tests proposed by Phillips et al. (2015) and Pavlidis et al. (2016). The recursive least-squares algorithm utilizes the matrix inversion lemma to avoid matrix inversion which results in significant speed improvements. Simulation of a variety of periodically-collapsing bubble processes.

Installation

# Install release version from CRAN
install.packages("exuber")

# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("kvasilopoulos/exuber")

If you encounter a clear bug, please file a reproducible example on GitHub.

Usage

{exuber} is based on two principles when testing for explosive dynamics in time series — estimating statistics and generating critical values.

Estimation

The radf() function offers a vectorized estimation (i.e. single and multiple time-series) for individual and panel estimation. The estimation can parse data from multiple classes and handle dates as index.

Critical Values

There are several options for generating critical values. On default {exuber} will use Monte Carlo simulated critical values if no other option is provided. The package offers these critical values in the form of data (up to 700 observations), that are obtain with the mc_cv() function. Alternatively, {exuber} accommodates Wild Bootstrapped and Sieve Bootstrapped (panel) critical values through wb_cv() and sb_cv() respectively.


Please note that the ‘exuber’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Functions in exuber

Name Description
radf Recursive Augmented Dickey-Fuller Test
%>% Pipe operator
tidy.mc_cv Tidy an cv object
summary Summarizing radf models
mc_cv Monte Carlo Critical Values
sb_cv Panel Sieve Bootstrap Critical Values
sim_blan Simulation of a Blanchard (1979) bubble process
sim_psy1 Simulation of a single-bubble process
sim_psy2 Simulation of a two-bubble process
exuber exuber: Econometric Analysis of Explosive Time Series
index.radf Retrieve/Replace the index
exuber-deprecated Deprecated functions in package exuber.
sim_evans Simulation of an Evans (1991) bubble process
sim_div Simulation of dividends
reexports Objects exported from other packages
wb_cv Wild Bootstrap Critical values
tidy.radf Tidy an radf object
psy_minw Helper functions in accordance to PSY(2015)
tidy.mc_distr Tidying *_dist objects
print.ggarrange Print a ggarrange object
calc_pvalue Calculate p-values
augment_join Tidy into a joint model
diagnostics Diagnostics
crit Simulated Monte Carlo critical values
col_names Retrieve/Set column names
autoplot.mc_distr Plotting distr object
datestamp Date-stamping periods of mildly explosive behavior
autoplot.datestamp Plotting and tidying datestamp objects
autoplot.radf Plotting and tidying radf objects
No Results!

Vignettes of exuber

Name
exuber.Rmd
plotting.Rmd
references.bib
simulation.Rmd
No Results!

Last month downloads

Details

Include our badge in your README

[![Rdoc](http://www.rdocumentation.org/badges/version/exuber)](http://www.rdocumentation.org/packages/exuber)