Provides a unified interface to extract trends, cycles, and
    seasonal components from monthly and quarterly time series using
    established econometric filters and smoothing methods, with
    frequency-aware defaults for common economic frequencies.

Provides a set of exploratory data analysis (EDA) tools for 
    visualizing trends, diagnosing data types for beginner-friendly workflows, 
    and automatically routing to suitable statistical tests or trend exploration 
    models. Includes unified plotting functions for trend lines, grouped boxplots, 
    and comparative scatterplots; automated statistical testing (e.g., t-test, 
    Wilcoxon, ANOVA, Kruskal-Wallis, Tukey, Dunn) with optional effect size 
    calculation; and model-based trend analysis using generalized additive 
    models (GAM) for count data, generalized linear models (GLM) for continuous 
    data, and zero-inflated models (ZIP/ZINB) for count data with potential 
    zero-inflation. 
    Also supports time-window continuity checks, cross-year 
    handling in compare_monthly_cases(), and ARIMA-ready preparation with 
    stationarity diagnostics, ensuring consistent parameter styles for 
    reproducible research and user-friendly workflows.Methods are 
    based on R Core Team (2024) <https://www.R-project.org/>, 
    Wood, S.N.(2017, ISBN:978-1498728331),
    Hyndman RJ, Khandakar Y (2008) <doi:10.18637/jss.v027.i03>, 
    Simon Jackman (2024) <https://github.com/atahk/pscl/>,    
    Achim Zeileis, Christian Kleiber, Simon Jackman (2008) <doi:10.18637/jss.v027.i08>.

Matrix factorization for multivariate time series with both low rank and temporal structures. 
    The procedure is the one proposed by Alquier, P. and Marie, N. 
    "Matrix factorization for multivariate time series analysis." 
    Electronic Journal of Statistics, 13(2), 4346-4366 (2019).

Non-parametric trend comparison of two independent samples with sequential subsamples. For more details, please refer to Wang, Stapleton, and Chen (2018) <doi:10.1080/00949655.2018.1482492>.