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license: GPL-3.0-or-later
title: 'trendtestR: Exploratory Trend Analysis and Visualization for Time-Series and
Grouped Data'
version: 1.0.1
doi: 10.32614/CRAN.package.trendtestR
abstract: 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) ,
Wood, S.N.(2017, ISBN:978-1498728331), Hyndman RJ, Khandakar Y (2008) ,
Simon Jackman (2024) , Achim Zeileis, Christian
Kleiber, Simon Jackman (2008) .
authors:
- name: Gelan Huang
email: huanggelan97@icloud.com
repository: https://grahnh.r-universe.dev
repository-code: https://github.com/GrahnH/trendtestR
commit: 123bae3bf28084abfcb5e8fdfdb6bde7e569d538
url: https://github.com/GrahnH/trendtestR
date-released: '2025-09-18'
contact:
- name: Gelan Huang
email: huanggelan97@icloud.com