Functions and data sets to perform and demonstrate community ecology statistical tests, including Hutcheson's t-test (Hutcheson (1970) <doi:10.1016/0022-5193(70)90124-4>, Zar (2010) ISBN:9780321656865).

An intuitive and user-friendly package designed to aid undergraduate students in understanding and applying econometric methods in their studies,
    Tailored specifically for Econometrics and Regression Modeling courses, it provides a practical toolkit for modeling and analyzing econometric data with detailed inference capabilities.

Production efficiency and economic efficiency are crucial concepts in agriculture/horticulture for sustainable and profitable practices. It helps to determine the optimal use of resources to maximize outputs and profitability. Production efficiency focuses on the optimal use of resources to produce goods, while economic efficiency ensures these goods are produced and allocated in a way that maximizes economic welfare. Production efficiency and economic efficiency are calculated with the help of the formula given by (Kumar et al., 2017) <doi:10.21921/jas.v4i04.10202>.

Implements three complementary pipelines for causal analysis on macroeconomic time series:
    (1) Error-Correction Models with Multivariate Adaptive Regression Splines (ECM-MARS),
    (2) Bayesian Structural Time Series (BSTS), and 
    (3) Bayesian GLM with AR(1) errors validated with Leave-Future-Out (LFO). 
    Heavy backends (Stan) are optional and never used in examples or tests.

The 'EconDataverse' is a universe of open-source packages to work 
    seamlessly with economic data. This package is designed to make it easy to 
    download selected datasets that are preprocessed by 'EconDataverse' packages 
    and publicly hosted on 'Hugging Face'. Learn more about the 'EconDataverse' 
    at <https://www.econdataverse.org>.

The 'EconDataverse' is a universe of open-source packages to work 
    seamlessly with economic data. This package is designed to make it easy to 
    install and load multiple 'EconDataverse' packages in a single step. Learn
    more about the 'EconDataverse' at <https://www.econdataverse.org>.