Package index • depictr

Exploring data

A first look at distributions, relationships, data quality and summaries.

Principal components, k-means and hierarchical clustering with cluster diagnostics, and Kaplan-Meier survival curves.

Series over time, autocorrelation, decomposition, seasonal subseries and forecasting.

timeseries_plot(): Time-series plot
acf_plot(): Autocorrelation plot
decompose_plot(): Time-series decomposition plot
seasonal_plot(): Seasonal-subseries (cycle) plot
ts_forecast(): Forecast a seasonal series with STL plus seasonal-naive drift

Forest plots, model comparison, predicted values, interactions, random effects and goodness-of-fit, built on a shared tidy estimate table.

tidy_estimates(): Extract a tidy table of estimates
coefficient_plot(): Forest (coefficient) plot
compare_models(): Compare estimates from several models or sources
frequentist_bayesian_plot(): Plot frequentist and Bayesian estimates together
effects_plot(): Plot predicted values for one predictor
interaction_plot(): Plot a two-way interaction of predicted values
random_effects_plot(): Caterpillar plot of random effects
optimizer_fixef_plot(): Plot fixed effects across optimisers
model_fit_table(): Goodness-of-fit statistics across models

Residual diagnostics, influence, and the standard classification curves and tables.

residual_diagnostics_plot(): Residual-diagnostics panel for a fitted model
binned_residual_plot(): Binned-residual plot for a generalised linear model
influence_plot(): Influence plot
qq_plot(): Normal quantile-quantile plot
vif_plot(): Variance inflation factor plot
roc_curve_plot(): ROC curve
pr_curve_plot(): Precision-recall curve
gain_plot(): Cumulative gains chart
lift_plot(): Cumulative lift chart
calibration_plot(): Calibration plot
threshold_plot(): Classification metrics versus decision threshold
confusion_matrix_plot(): Confusion matrix heatmap

Posterior summaries and power analysis curves.

A shared theme and colourblind-aware palette, label helpers, plot composition and saving, and a one-figure model report.

theme_depictr(): The depictr ggplot2 theme
depictr_palette(): The depictr colour palettes
scale_colour_depictr() scale_color_depictr() scale_fill_depictr(): depictr colour and fill scales
palette_preview(): Preview the depictr palettes
format_terms(): Tidy raw coefficient names for display
model_report(): A one-figure model report
arrange_plots(): Compose several plots into one figure
save_plot(): Save a plot with publication-ready defaults
depictr_options(): Get or set the depictr look-and-feel options

Reproducibly simulated datasets used throughout the documentation.