(>= 0.17.1), paletteer, parameters (>= 0.17.0), patchwork,
performance, purrr, rlang, stats, statsExpressions (>= 1.3.2),
Suggests: afex, BayesFactor (>= 0.9.12-4.3), gapminder, ggcorrplot,
ggside, knitr, lme4, MASS, metaBMA, metafor, PMCMRplus, psych,
rmarkdown, spelling, survival, testthat (>= 3.1.4), tibble,
Packaged: 2022-05-21 09:54:06 UTC; indrajeetpatil

Imports: correlation (>= 0.8.1), dplyr, ggplot2, ggrepel, ggsignif,
glue, insight (>= 0.17.1), paletteer, parameters (>= 0.18.0),
patchwork, performance, purrr, rlang, stats, statsExpressions
Packaged: 2022-05-26 17:47:27 UTC; indrajeetpatil

Imports: correlation (>= 0.8.2), datawizard (>= 0.5.0), dplyr, ggplot2,
ggrepel, ggsignif, glue, insight (>= 0.18.2), paletteer,
parameters (>= 0.18.2), patchwork, performance (>= 0.9.2),
purrr, rlang, stats, statsExpressions (>= 1.3.3), tidyr, utils
Suggests: afex, BayesFactor (>= 0.9.12-4.4), gapminder, ggcorrplot,
ggside, knitr, lme4, MASS, metaBMA, metafor, metaplus,
PMCMRplus, psych, rmarkdown, spelling, survival, testthat (>=
Packaged: 2022-08-11 13:09:05 UTC; indrajeetpatil

Imports: correlation (>= 0.8.3), datawizard (>= 0.6.2), dplyr, ggplot2,
ggrepel, ggsignif, glue, insight (>= 0.18.5), paletteer,
parameters (>= 0.19.0), patchwork, performance (>= 0.10.0),
purrr, rlang, stats, statsExpressions (>= 1.3.4), tidyr, utils
Packaged: 2022-10-16 07:24:25 UTC; indrajeetpatil

Description: Make smoothed stacked area charts in 'ggplot2'. Stream plots are useful to show magnitude trends over time.
Imports: ggplot2, purrr, dplyr, stats, magrittr, tidyr, forcats
Packaged: 2021-05-04 17:27:21 UTC; davidsjoberg

Title: Continuous Confidence Interval Plots using t-Distribution
Description: Provides an extension to 'ggplot2' (Wickham, 2016, <doi:10.1007/978-3-319-24277-4>) for creating two
types of continuous confidence interval plots (Violin CI and Gradient CI plots), typically for the sample mean.
These plots contain multiple user-defined confidence areas with varying colours,
defined by the underlying t-distribution used to compute standard confidence intervals for
the mean of the normal distribution when the variance is unknown.
Two types of plots are available, a gradient plot with rectangular areas, and a violin plot where the
shape (horizontal width) is defined by the probability density function of the t-distribution.