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NRMstatsML: Statistical and Machine Learning Engine for Long-Term Natural Resource Management Data

A comprehensive toolkit for statistical and machine learning-based analysis of long-term Natural Resource Management (NRM) datasets. Integrates formula-driven approaches, statistical inference, and machine learning (ML) models for advanced analytics. Modules cover trend and structural analysis (Mann-Kendall test, slope estimation, Chow test, structural break detection), multivariate system modelling (Partial Least Squares (PLS), Structural Equation Modelling (SEM)), response curve optimisation, time-series forecasting (Autoregressive Integrated Moving Average (ARIMA), hybrid models), panel data and treatment effects (Difference-in-Differences (DiD), causal machine learning), uncertainty and sensitivity analysis (bootstrap, Monte Carlo, Bayesian), and automated model selection and performance comparison. Designed for long-term datasets covering soil, water, crop, and climate domains. Key references: Mann and Kendall (1945) <doi:10.2307/1907187>; Sen (1968) <doi:10.1080/01621459.1968.10480934>; Bai and Perron (2003) <doi:10.1002/jae.659>; Rosseel (2012) <doi:10.18637/jss.v048.i02>; Croissant and Millo (2008) <doi:10.18637/jss.v027.i02>.

Version: 0.1.4
Depends: R (≥ 4.1.0)
Imports: Kendall (≥ 2.2), trend (≥ 1.1.4), strucchange (≥ 1.5.3), plm (≥ 2.6.0), forecast (≥ 8.20), lavaan (≥ 0.6.12), pls (≥ 2.8.0), caret (≥ 6.0.93), boot (≥ 1.3.28), ggplot2 (≥ 3.4.0), rlang (≥ 1.1.0), stats, utils
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, keras, tensorflow, BayesianTools, sensitivity, mboost, mlr3, covr
Published: 2026-06-07
DOI: 10.32614/CRAN.package.NRMstatsML
Author: Sadikul Islam ORCID iD [aut, cre, cph]
Maintainer: Sadikul Islam <sadikul.islamiasri at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: no
Language: en-US
Citation: NRMstatsML citation info
Materials: README, NEWS
CRAN checks: NRMstatsML results

Documentation:

Reference manual: NRMstatsML.html , NRMstatsML.pdf
Vignettes: Advanced Modelling Workflows with NRMstatsML (source, R code)
Getting Started with NRMstatsML (source, R code)

Downloads:

Package source: NRMstatsML_0.1.4.tar.gz
Windows binaries: r-devel: NRMstatsML_0.1.4.zip, r-release: NRMstatsML_0.1.4.zip, r-oldrel: NRMstatsML_0.1.4.zip
macOS binaries: r-release (arm64): NRMstatsML_0.1.4.tgz, r-oldrel (arm64): NRMstatsML_0.1.4.tgz, r-release (x86_64): NRMstatsML_0.1.4.tgz, r-oldrel (x86_64): NRMstatsML_0.1.4.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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