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NEWS.md

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# exuber 1.1.0
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* Fixed \link{} targets not in the package itself nor in the base packages to
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use package anchors, i.e., use \link[PKG]{FOO}
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# exuber 1.0.1
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Maintenance release to accommodate breaking changes in dplyr 1.1.0.

README.md

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<!-- badges: start -->
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[![CRAN status](https://www.r-pkg.org/badges/version/exuber)](https://CRAN.R-project.org/package=exuber)
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[![CRAN
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status](https://www.r-pkg.org/badges/version/exuber)](https://CRAN.R-project.org/package=exuber)
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[![Project Status: Active – The project has reached a stable, usable
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state and is being actively
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developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
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[![Lifecycle:
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stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
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[![R-CMD-check](https://github.com/kvasilopoulos/exuber/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/kvasilopoulos/exuber/actions/workflows/R-CMD-check.yaml)
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[![Codecov test coverage](https://codecov.io/gh/kvasilopoulos/exuber/graph/badge.svg)](https://app.codecov.io/gh/kvasilopoulos/exuber)
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[![Codecov test
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coverage](https://codecov.io/gh/kvasilopoulos/exuber/graph/badge.svg)](https://app.codecov.io/gh/kvasilopoulos/exuber)
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<!-- badges: end -->
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Testing for and dating periods of explosive dynamics (exuberance) in
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Testing for explosive dynamics is comprised of two distinct parts :
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- Estimation
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- Critical Values
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- Estimation
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- Critical Values
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**Some Context:** Conventional testing techniques compute critical
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values,and p-values from a standard distribution, where the user does
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The cornerstone function of the package is:
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- `radf()`: Recursive Augmented Dickey-Fuller Test.
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- `radf()`: Recursive Augmented Dickey-Fuller Test.
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This function offers a vectorized estimation (i.e. single and/or
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multiple time-series) for individual and panel estimation. The
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There are several options for generating critical values:
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- `radf_mc_cv()`: Monte Carlo
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- `radf_wb_cv()`: Wild Bootstrap
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- `radf_sb_cv()`: Sieve Bootstrap (Panel)
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- `radf_mc_cv()`: Monte Carlo
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- `radf_wb_cv()`: Wild Bootstrap
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- `radf_sb_cv()`: Sieve Bootstrap (Panel)
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On default `exuber` will use Monte Carlo simulated critical values if no
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other option is provided. The package offers these critical values in
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(`object`) and critical values (`cv`). The below methods break the
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process into small simple steps:
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- `summary()` summarizes the model.
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- `diagnostics()` shows which series reject the null hypothesis .
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- `datestamp()` computes the origination, termination and duration of
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episodes (if any).
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- `summary()` summarizes the model.
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- `diagnostics()` shows which series reject the null hypothesis .
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- `datestamp()` computes the origination, termination and duration of
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episodes (if any).
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These combined provide a comprehensive analysis on the exuberant
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behavior of the model.
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summary(rsim_data)
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#> Using `radf_crit` for `cv`.
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#>
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#> -- Summary (minw = 19, lag = 0) ------------------- Monte Carlo (nrep = 2000) --
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#> ── Summary (minw = 19, lag = 0) ─────────────────── Monte Carlo (nrep = 2000) ──
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#>
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#> psy1 :
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#> # A tibble: 3 x 5
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#> # A tibble: 3 × 5
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#> stat tstat `90` `95` `99`
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#> <fct> <dbl> <dbl> <dbl> <dbl>
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#> 1 adf -2.46 -0.413 -0.0812 0.652
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#> 2 sadf 1.95 0.988 1.29 1.92
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#> 3 gsadf 5.19 1.71 1.97 2.57
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#>
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#> psy2 :
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#> # A tibble: 3 x 5
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#> # A tibble: 3 × 5
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#> stat tstat `90` `95` `99`
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#> <fct> <dbl> <dbl> <dbl> <dbl>
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#> 1 adf -2.86 -0.413 -0.0812 0.652
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#> 2 sadf 7.88 0.988 1.29 1.92
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#> 3 gsadf 7.88 1.71 1.97 2.57
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#>
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#> evans :
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#> # A tibble: 3 x 5
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#> # A tibble: 3 × 5
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#> stat tstat `90` `95` `99`
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#> <fct> <dbl> <dbl> <dbl> <dbl>
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#> 1 adf -5.83 -0.413 -0.0812 0.652
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#> 2 sadf 5.28 0.988 1.29 1.92
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#> 3 gsadf 5.99 1.71 1.97 2.57
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#>
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#> div :
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#> # A tibble: 3 x 5
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#> # A tibble: 3 × 5
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#> stat tstat `90` `95` `99`
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#> <fct> <dbl> <dbl> <dbl> <dbl>
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#> 1 adf -1.95 -0.413 -0.0812 0.652
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#> 2 sadf 1.11 0.988 1.29 1.92
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#> 3 gsadf 1.34 1.71 1.97 2.57
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#>
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#> blan :
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#> # A tibble: 3 x 5
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#> # A tibble: 3 × 5
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#> stat tstat `90` `95` `99`
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#> <fct> <dbl> <dbl> <dbl> <dbl>
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#> 1 adf -5.15 -0.413 -0.0812 0.652
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diagnostics(rsim_data)
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#> Using `radf_crit` for `cv`.
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#>
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#> -- Diagnostics (option = gsadf) --------------------------------- Monte Carlo --
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#> ── Diagnostics (option = gsadf) ───────────────────────────────── Monte Carlo ──
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#>
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#> psy1: Rejects H0 at the 1% significance level
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#> psy2: Rejects H0 at the 1% significance level
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datestamp(rsim_data)
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#> Using `radf_crit` for `cv`.
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#>
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#> -- Datestamp (min_duration = 0) --------------------------------- Monte Carlo --
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#> ── Datestamp (min_duration = 0) ───────────────────────────────── Monte Carlo ──
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#>
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#> psy1 :
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#> Start Peak End Duration Signal Ongoing

cran-comments.md

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This is a maintenance submission to deal with warnings from dplyr 1.1.0.
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## Test environments
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* local OS MS install, R 4.2.2
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* local OS MS install, R 4.3.2
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* Continuous Integration
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* GitHub actions (ubuntu-20.04): release, devel
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* GitHub actions (windows): release
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* Github actions (OS X): release
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* Rhub
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* Debian Linux, R-devel, GCC ASAN/UBSAN
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* Fedora Linux, R-devel, clang, gfortran
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* win-builder (devel)
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* win-builder (release)
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## R CMD check results
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### rhub::check_for_cran() & devtools::check_win_devel() & rcmdcheck::rcmdcheck(env = c("_R_CHECK_RD_VALIDATE_RD2HTML_" = "TRUE"))
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0 ERRORS √ | 0 WARNINGS √ | 2 NOTEs
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```r

man/figures/usage-1.png

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