Package index

Targets and Core Elicitation

Canonical target construction and K-based calibration

DPprior_target_K()

Construct a Canonical Bounded-Discrete Cluster-Count Target

DPprior_fit()

Fit a Gamma hyperprior from an occupied-cluster target

Dual-Anchor Calibration

Current hard and soft workflows plus the retained v2.x legacy adapter

DPprior_dual_hard()

Dual-anchor calibration with a verified hard inequality

DPprior_dual_soft()

Calibrate a fixed-scale soft Dual-Anchor trade-off

DPprior_dual()

Legacy Dual-Anchor equality-loss adapter

Schema Migration

Conservative validation and upgrade of serialized objects

upgrade_DPprior_object()

Upgrade a serialized DPprior object conservatively

Approximation Algorithms

A1 closed-form and A2 Newton-based algorithms

DPprior_a1()

A1 Closed-Form Prior Elicitation

DPprior_a2_newton()

A2-MN Calibrated-Moment Newton Solver

DPprior_a2_kl()

A2-KL: KL Divergence Minimization for Prior Calibration

Stirling Numbers

Computation of unsigned Stirling numbers of the first kind

compute_log_stirling()

Compute Log Stirling Numbers (First Kind, Unsigned)

K Distribution (Conditional)

Antoniak distribution P(K | alpha)

pmf_K_given_alpha()

PMF of K Given Alpha (Antoniak Distribution)

log_pmf_K_given_alpha()

Log-PMF of K Given Alpha (Antoniak Distribution)

cdf_K_given_alpha()

CDF of K Given Alpha

mean_K_given_alpha()

Conditional Mean of K_J Given Alpha

var_K_given_alpha()

Conditional Variance of K_J Given Alpha

mode_K_given_alpha()

Mode of K Given Alpha

quantile_K_given_alpha()

Quantile of K Given Alpha

moments_K_given_alpha()

Conditional Mean and Variance of K_J Given Alpha

cv_K_given_alpha()

Coefficient of Variation for K Given Alpha

dispersion_K_given_alpha()

Dispersion Index for K Given Alpha

K Distribution (Marginal)

Marginal distribution of K under Gamma prior on alpha

pmf_K_marginal()

Marginal PMF of K_J under Gamma Hyperprior

cdf_K_marginal()

CDF of Marginal K Distribution

mode_K_marginal()

Mode of Marginal K Distribution

quantile_K_marginal()

Quantile of Marginal K Distribution

summary_K_marginal()

Summary Statistics for Marginal K Distribution

K_moments()

Convenience Wrapper for Marginal Moments

exact_K_moments()

Marginal Moments of K_J under Gamma Prior

Weight Distribution (w1)

Distribution of the first stick-breaking / size-biased weight

mean_w1()

Mean of the First Size-Biased DP Weight

var_w1()

Variance of the First Size-Biased DP Weight

prob_wsb_exceeds()

Tail Probability of the First Size-Biased DP Weight

prob_w1_exceeds()

Tail Probability of the First Size-Biased DP Weight

quantile_w1()

Quantile Function of the First Size-Biased DP Weight

density_w1()

Density of the First Size-Biased DP Weight

cdf_w1()

CDF of the First Size-Biased DP Weight

rw1()

Random Generation from the First Size-Biased DP Weight Distribution

summary_w1()

Summary Statistics for the First Size-Biased DP Weight

w1_grid()

Compute the First Size-Biased DP Weight Distribution on a Grid

Maximum-Weight Tail Bounds

Certified W-max bounds and the status-aware deferred direct interface

wmax_tail_bounds()

Certified Bounds for the Largest DP Population Weight Tail

prob_wmax_exceeds()

Largest DP Population Weight Tail Probability

Co-clustering Probability (rho)

Pairwise co-clustering probability functions

mean_rho()

Marginal Mean of rho

var_rho()

Marginal Variance of rho

mean_rho_given_alpha()

Conditional Mean of rho Given Alpha

var_rho_given_alpha()

Conditional Variance of rho Given Alpha

cv_rho()

Coefficient of Variation of rho

rrho()

Random Generation from rho Distribution

summary_rho()

Summary Statistics for rho Distribution

rho_conditional_grid()

Compute rho Conditional Moments on alpha Grid

Diagnostics

Prior validation and diagnostic tools

DPprior_diagnostics()

Comprehensive Prior Diagnostics

DPprior_error_bounds()

Compute A1 Approximation Error Bounds

check_dominance_risk()

Deprecated Ambiguous Weight-Risk Check

dual_anchor_diagnostics()

Compare a Dual-Anchor fit with its K-only start

compare_a1_a2()

Compare A1 vs A2 Accuracy

Visualization

Plotting functions

plot(<DPprior_fit>)

Plot Method for DPprior_fit Objects

plot_alpha_prior()

Plot Prior Density of Alpha

plot_K_prior()

Plot Prior PMF of K_J

plot_w1_prior()

Plot Prior Density of the First Size-Biased DP Weight

plot_prior_dashboard()

4-Panel Prior Dashboard

plot_dual_comparison()

Plot Dual-Anchor Comparison Dashboard

plot_dual_dashboard()

Plot Canonical Dual Comparison Dashboard

plot_tradeoff_curve()

Plot Trade-off Curve

plot_tradeoff_dashboard()

Plot Trade-off Multi-Panel

DPprior_colors()

DPprior Color Palette

theme_DPprior()

Publication-Quality Theme for DPprior Plots

S3 Methods

Print, summary, and coercion methods

print(<DPprior_fit>)

Print Method for DPprior_fit Objects

summary(<DPprior_fit>)

Summary Method for DPprior_fit Objects

print(<summary.DPprior_fit>)

Print Method for summary.DPprior_fit

as.data.frame(<DPprior_fit>)

Coerce a canonical DPprior fit to a data frame

print(<DPprior_diagnostics>)

Print Method for DPprior_diagnostics Objects

summary(<DPprior_diagnostics>)

Summary Method for DPprior_diagnostics Objects

as.data.frame(<DPprior_diagnostics>)

Data-Frame Method for DPprior_diagnostics Objects

print(<DPprior_error_bounds>)

Print Method for DPprior_error_bounds Objects

summary(<DPprior_error_bounds>)

Summary Method for DPprior_error_bounds Objects

print(<w1_summary>)

Print Method for w1_summary Objects

print(<rho_summary>)

Print Method for rho_summary Objects

Numerical Utilities

Conversion, quadrature, and numerical helper functions

vif_to_variance()

Convert Variance Inflation Factor to Variance

confidence_to_vif()

Map a Qualitative Confidence Level to a Variance Inflation Factor (VIF)

cv_alpha_to_variance()

Convert CV(alpha) to Variance

integrate_gamma()

Integrate Function Against Gamma Distribution

build_gamma_quadrature()

Build Quadrature for Gamma(a, b) Integration

gauss_laguerre_nodes()

Gauss-Laguerre Quadrature Nodes and Weights

logsumexp()

Numerically Stable Log-Sum-Exp (Binary)

logsumexp_vec()

Vectorized Log-Sum-Exp

score_a()

Score Function with Respect to Shape Parameter a

score_b()

Score Function with Respect to Rate Parameter b

Computation

Lower-level computational functions

compute_weight_diagnostics()

First size-biased and largest-weight diagnostics

compute_error_landscape()

Compute A1 Error Landscape

compute_tradeoff_curve()

Compute a status-aware soft trade-off path

compute_scaling_constant()

Compute Scaling Constant for A1 Mapping

a1_moment_error()

A1 Approximation Moment Errors

discretize_chisq()

Discretize Chi-Square to K_J Support

kl_divergence_K()

KL Divergence Between Target and Induced K_J PMFs

kl_divergence_pmf()

KL Divergence Between Two PMFs

moments_with_jacobian()

Compute Marginal Moments and Jacobian Simultaneously

Validation & Verification

Functions for verifying mathematical properties

validate_stirling()

Validate Stirling Number Computation

verify_jacobian()

Verify Jacobian Against Finite Differences

verify_underdispersion()

Verify Underdispersion Inequality