Package index • bayesiansurpriser

Core Functions

Main functions for computing Bayesian Surprise

surprise(): Compute Bayesian Surprise

compute_surprise(): Compute Per-Region Surprise

auto_surprise(): Compute Surprise with Automatic Model Selection

st_surprise(): Compute Surprise for sf Object

Model Constructors

Create probability models for the model space

bs_model_uniform(): Create a Uniform Model

bs_model_baserate(): Create a Base Rate Model

bs_model_baserate_col(): Create Base Rate 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_funnel(): Create a de Moivre Funnel Model

bs_model_funnel_col(): Create Funnel Model from Column

bs_model_bootstrap(): Create a Bootstrap Sample Model

Model Space

Combine models and manage priors

model_space(): Create a Model Space

default_model_space(): Default Model Space

add_model(): Add Model to Space

remove_model(): Remove Model from Space

set_prior(): Set Prior Probabilities

model_names(): Get Model Names

n_models(): Get Number of Models

Bayesian Updates

Update beliefs with new data

bayesian_update(): Bayesian Update of Model Space

cumulative_bayesian_update(): Global Bayesian Update Across All Regions

update_surprise(): Update Surprise with New Data (Streaming)

Temporal Analysis

Analyze surprise over time

surprise_temporal(): Compute Temporal Surprise

surprise_rolling(): Rolling Window Surprise

surprise_animate(): Create Animation-Ready Data from Temporal Results

get_surprise_at_time(): Get Surprise at Specific Time

Funnel Plot Utilities

Tools for funnel plot analysis

compute_funnel_data(): Compute Funnel Plot Data

funnel_zscore(): Funnel Z-Score (de Moivre)

funnel_pvalue(): Compute P-Value from Funnel Z-Score

Result Accessors

Extract values from surprise results

get_surprise(): Extract surprise values from result objects

get_model_space(): Get the model space from a surprise result

Plot Methods

Base R plotting methods for surprise objects

plot(<bs_surprise>): Plot Surprise Result

plot(<bs_surprise_sf>): Plot Surprise Map (sf)

plot(<bs_surprise_temporal>): Plot Temporal Surprise

plot(<bs_model_space>): Plot Model Space

Spatial Functions

Integration with sf spatial data

st_surprise(): Compute Surprise for sf Object

st_density(): Spatial Density Estimation for sf Objects

st_density_at(): Evaluate Density at sf Feature Locations

st_aggregate_surprise(): Aggregate Surprise to Larger Regions

ggplot2 Scales

Color scales for visualizing surprise

scale_fill_surprise() scale_colour_surprise() scale_color_surprise(): Surprise Color Scale (Sequential)

scale_fill_surprise_diverging() scale_colour_surprise_diverging() scale_color_surprise_diverging(): Signed Surprise Color Scale (Diverging)

scale_fill_surprise_binned() scale_colour_surprise_binned() scale_color_surprise_binned(): Binned Surprise Scale

scale_fill_surprise_diverging_binned(): Binned Diverging Surprise Scale

scale_fill_surprise_thresholds() scale_colour_surprise_thresholds() scale_color_surprise_thresholds(): Signed Surprise Scale with Meaningful Thresholds

scale_fill_surprise_manual(): Manual Surprise Breaks Scale

ggplot2 Geoms and Stats

Geometric objects and statistics for ggplot2

geom_surprise(): Surprise Map Geom

geom_surprise_histogram(): Surprise Histogram

geom_surprise_density(): Surprise Density Plot

stat_surprise(): Compute Surprise as ggplot2 Stat

stat_surprise_sf(): Stat for Surprise with sf Geometries

StatSurprise: StatSurprise ggproto Object

StatSurpriseSf: StatSurpriseSf ggproto Object (for sf integration)

Normalization Utilities

Data normalization functions

normalize_prob(): Normalize to Probability Distribution

normalize_rate(): Normalize to Rate (Per Capita)

normalize_zscore(): Z-Score Normalization

normalize_minmax(): Min-Max Normalization

normalize_robust(): Robust Normalization (using quantiles)

Mathematical Utilities

Low-level mathematical functions

kl_divergence(): Kullback-Leibler Divergence

log_sum_exp(): Log-Sum-Exp (Numerically Stable)

Sample Data

Example datasets included with the package

canada_mischief: Canadian Mischief Crime Data by Province

example_counties: Example County Data with Simulated Events