# exuber v0.3.0

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## 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.

# exuber

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!