Package: easyViz
Title: Easy Visualization of Conditional Effects from Regression Models
Version: 1.1.0
Authors@R: person("Luca", "Corlatti", role = c("aut", "cre"), email="lucac1980@yahoo.it")
Description: Offers a flexible and user-friendly interface for visualizing conditional 
 effects from a broad range of regression models, including mixed-effects and generalized 
 additive (mixed) models. Compatible model types include lm(), rlm(), glm(), glm.nb(), 
 and gam() (from 'mgcv'); nonlinear models via nls(); and generalized least squares via 
 gls(). Mixed-effects models with random intercepts and/or slopes can be fitted using 
 lmer(), glmer(), glmer.nb(), glmmTMB(), or gam() (from 'mgcv', via smooth terms). 
 Plots are rendered using base R graphics with extensive customization options. 
 Approximate confidence intervals for nls() models are computed using the delta method.
 Robust standard errors for rlm() are computed using the sandwich estimator (Zeileis 2004) 
 <doi:10.18637/jss.v011.i10>. Methods for generalized additive models follow Wood (2017) 
 <doi:10.1201/9781315370279>. For linear mixed-effects models with 'lme4', see 
 Bates et al. (2015) <doi:10.18637/jss.v067.i01>. For mixed models using 'glmmTMB', 
 see Brooks et al. (2017) <doi:10.32614/RJ-2017-066>. 
Maintainer: Luca Corlatti <lucac1980@yahoo.it>
Imports: stats, utils, graphics, grDevices
Suggests: nlme, lme4, MASS, glmmTMB, mgcv, numDeriv, sandwich
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-08-21 19:19:35 UTC; lucacorlatti
Author: Luca Corlatti [aut, cre]
Repository: CRAN
Date/Publication: 2025-08-21 19:42:05 UTC
Built: R 4.4.3; ; 2025-11-01 02:27:50 UTC; windows
