MAARTS: Merger and Acquisition Autoregressive Time-Series Models
Implements comprehensive Merger and Acquisition ('M&A')
Autoregressive ('AR') time-series models with full statistical analysis
capabilities. The package provides parameter estimation, forecasting
with confidence intervals (80%, 90%, 95%, 99%), descriptive statistics,
stationarity tests (Augmented Dickey-Fuller ('ADF'), Phillips-Perron,
Kwiatkowski-Phillips-Schmidt-Shin ('KPSS'),
Dickey-Fuller Generalized Least Squares ('DF-GLS')), autocorrelation
analysis (Autocorrelation Function ('ACF'),
Partial Autocorrelation Function ('PACF')), model diagnostics
(Ljung-Box, Box-Pierce), accuracy measures
(Mean Squared Error ('MSE'), Mean Absolute Error ('MAE'),
Mean Absolute Scaled Error ('MASE'),
Root Mean Squared Error ('RMSE'),
Symmetric Mean Absolute Percentage Error ('SMAPE'), F-statistic),
residual diagnostics (normality tests, heteroscedasticity tests),
model stability analysis, impulse response, information criteria
(Akaike Information Criterion ('AIC'),
Bayesian Information Criterion ('BIC'),
Hannan-Quinn Information Criterion ('HQIC')),
structural break analysis, spectral analysis, and Monte Carlo simulation.
Models are based on:
Kumar, Mudassir, and Agiwal (2024)
<https://ph02.tci-thaijo.org/index.php/thaistat/article/view/253436>,
Kumar, Mudassir, and Srivastava (2025) <doi:10.1007/s44199-025-00104-3>,
Kumar and Mudassir (2025) <doi:10.19139/soic-2310-5070-2029>.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
forecast, tseries, urca, stats, graphics, grDevices, utils, lmtest, sandwich, nortest, moments, strucchange, ggplot2, gridExtra, MASS, numDeriv |
| Suggests: |
testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-07-26 |
| DOI: |
10.32614/CRAN.package.MAARTS (may not be active yet) |
| Author: |
Shikhar Tyagi 
[aut, cre],
Mohd Mudassir [aut],
Vrijesh Tripathi [aut] |
| Maintainer: |
Shikhar Tyagi <shikhar1093tyagi at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Language: |
en-US |
| CRAN checks: |
MAARTS results |
Documentation:
Downloads:
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