R: Bayesian Surprise for De-Biasing Thematic Maps

# Bayesian Surprise for De-Biasing Thematic Maps

## Documentation for package ‘bayesiansurpriser’ version 0.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

add_model | Add Model to Space
auto_surprise | Compute Surprise with Automatic Model Selection
bayesian_update | Bayesian Update of Model Space
bs_model_baserate | Create a Base Rate Model
bs_model_baserate_col | Create Base Rate Model from Column
bs_model_bootstrap | Create a Bootstrap Sample Model
bs_model_funnel | Create a de Moivre Funnel Model
bs_model_funnel_col | Create Funnel Model from Column
bs_model_gaussian | Create a Gaussian Model
bs_model_gaussian_mixture | Create Multi-Modal Gaussian Mixture Model
bs_model_sampled | Create a Sampled Subset Model (KDE)
bs_model_uniform | Create a Uniform Model
canada_mischief | Canadian Mischief Crime Data by Province
compute_funnel_data | Compute Funnel Plot Data
compute_surprise | Compute Per-Region Surprise
cumulative_bayesian_update | Global Bayesian Update Across All Regions
default_model_space | Default Model Space
example_counties | Example County Data with Simulated Events
funnel_pvalue | Compute P-Value from Funnel Z-Score
funnel_zscore | Funnel Z-Score (de Moivre)
geom_surprise | Surprise Map Geom
geom_surprise_density | Surprise Density Plot
geom_surprise_histogram | Surprise Histogram
get_model_space | Get the model space from a surprise result
get_surprise | Extract surprise values from result objects
get_surprise_at_time | Get Surprise at Specific Time
kl_divergence | Kullback-Leibler Divergence
log_sum_exp | Log-Sum-Exp (Numerically Stable)
model_names | Get Model Names
model_space | Create a Model Space
normalize_minmax | Min-Max Normalization
normalize_prob | Normalize to Probability Distribution
normalize_rate | Normalize to Rate (Per Capita)
normalize_robust | Robust Normalization (using quantiles)
normalize_zscore | Z-Score Normalization
n_models | Get Number of Models
plot.bs_model_space | Plot Model Space
plot.bs_surprise | Plot Surprise Result
plot.bs_surprise_sf | Plot Surprise Map (sf)
plot.bs_surprise_temporal | Plot Temporal Surprise
remove_model | Remove Model from Space
scale_color_surprise | Surprise Color Scale (Sequential)
scale_color_surprise_binned | Binned Surprise Scale
scale_color_surprise_diverging | Signed Surprise Color Scale (Diverging)
scale_color_surprise_thresholds | Signed Surprise Scale with Meaningful Thresholds
scale_colour_surprise | Surprise Color Scale (Sequential)
scale_colour_surprise_binned | Binned Surprise Scale
scale_colour_surprise_diverging | Signed Surprise Color Scale (Diverging)
scale_colour_surprise_thresholds | Signed Surprise Scale with Meaningful Thresholds
scale_fill_surprise | Surprise Color Scale (Sequential)
scale_fill_surprise_binned | Binned Surprise Scale
scale_fill_surprise_diverging | Signed Surprise Color Scale (Diverging)
scale_fill_surprise_diverging_binned | Binned Diverging Surprise Scale
scale_fill_surprise_manual | Manual Surprise Breaks Scale
scale_fill_surprise_thresholds | Signed Surprise Scale with Meaningful Thresholds
set_prior | Set Prior Probabilities
stat_surprise | Compute Surprise as ggplot2 Stat
stat_surprise_sf | Stat for Surprise with sf Geometries
st_density | Spatial Density Estimation for sf Objects
st_density_at | Evaluate Density at sf Feature Locations
st_surprise | Compute Surprise for sf Object
surprise | Compute Bayesian Surprise
surprise.data.frame | Compute Bayesian Surprise
surprise.sf | Compute Bayesian Surprise
surprise.tbl_df | Compute Bayesian Surprise
surprise_animate | Create Animation-Ready Data from Temporal Results
surprise_rolling | Rolling Window Surprise
surprise_temporal | Compute Temporal Surprise
update_surprise | Update Surprise with New Data (Streaming)