Package index • beezdemand

Modern Model Fitting

Recommended functions for fitting demand models. These return structured S3 objects with consistent methods for inspection and inference.

fit_demand_fixed(): Fit Fixed-Effect Demand Curves
fit_demand_mixed(): Fit Nonlinear Mixed-Effects Demand Model
fit_demand_hurdle(): Fit Two-Part Mixed Effects Hurdle Demand Model
fit_cp_nls(): Fit cross-price demand with NLS (+ robust fallbacks)
fit_cp_linear() fit_cp_linear.default() fit_cp_linear.mixed(): Fit a Linear Cross-Price Demand Model

Legacy Model Fitting

Original functions for demand curve fitting. These are superseded by modern alternatives but remain available for backward compatibility.

FitCurves(): FitCurves
FitMeanCurves(): Fit Pooled/Mean Curves

Data Quality & Screening

Functions for checking systematic responding patterns in demand data.

check_systematic_demand(): Check Demand Data for Unsystematic Responding
check_systematic_cp(): Check Cross-Price Data for Unsystematic Responding
CheckUnsystematic(): Systematic Purchase Task Data Checker
check_unsystematic_cp(): Check for Unsystematic Patterns in Cross-Price Data

Data Preparation

Functions for preparing and transforming demand data.

pivot_demand_data(): Reshape Demand Data Between Wide and Long Formats
ChangeData(): ChangeData
ReplaceZeros(): Replace Zeros
CheckCols(): Check Column Names
RecodeOutliers(): Recode Outliers

Model Inspection

S3 methods for extracting information from fitted models.

tidy(<beezdemand_fixed>): Tidy Method for beezdemand_fixed
tidy(<beezdemand_hurdle>): Tidy a beezdemand_hurdle Model
tidy(<beezdemand_nlme>): Tidy method for beezdemand_nlme
tidy(<beezdemand_systematicity>): Tidy Method for beezdemand_systematicity
tidy(<cp_model_lm>): Extract coefficients from a linear cross-price model in tidy format
tidy(<cp_model_lmer>): Extract coefficients from a mixed-effects cross-price model in tidy format
tidy(<cp_model_nls>): Convert a cross-price model to a tidy data frame of coefficients
glance(<beezdemand_fixed>): Glance Method for beezdemand_fixed
glance(<beezdemand_hurdle>): Glance at a beezdemand_hurdle Model
glance(<beezdemand_nlme>): Glance method for beezdemand_nlme
glance(<beezdemand_systematicity>): Glance Method for beezdemand_systematicity
glance(<cp_model_lm>): Get model summaries from a linear cross-price model
glance(<cp_model_lmer>): Get model summaries from a mixed-effects cross-price model
glance(<cp_model_nls>): Get model summaries from a cross-price model
augment(<beezdemand_fixed>): Augment a beezdemand_fixed Model with Fitted Values and Residuals
augment(<beezdemand_hurdle>): Augment a beezdemand_hurdle Model with Fitted Values and Residuals
augment(<beezdemand_nlme>): Augment a beezdemand_nlme Model with Fitted Values and Residuals
confint(<beezdemand_fixed>): Confidence Intervals for Fixed-Effect Demand Model Parameters
confint(<beezdemand_hurdle>): Confidence Intervals for Hurdle Demand Model Parameters
confint(<beezdemand_nlme>): Confidence Intervals for Mixed-Effects Demand Model Parameters
confint(<cp_model_nls>): Confidence Intervals for Cross-Price NLS Model Parameters
coef(<cp_model_nls>) coef(<cp_model_lm>) coef(<cp_model_lmer>): Extract Coefficients from Cross-Price Demand Models
coef(<beezdemand_fixed>): Extract Coefficients from Fixed-Effect Demand Fit
coef(<beezdemand_hurdle>): Extract Coefficients from Hurdle Demand Model
coef(<beezdemand_nlme>): Extract Coefficients from a beezdemand_nlme Model
fixef(<beezdemand_nlme>): Extract Fixed Effects from a beezdemand_nlme Model
fixef(<cp_model_lmer>): Extract Fixed Effects from Mixed-Effects Cross-Price Model
ranef(<beezdemand_nlme>): Extract Random Effects from a beezdemand_nlme Model
ranef(<cp_model_lmer>): Extract Random Effects from Mixed-Effects Cross-Price Model
AIC(<beezdemand_hurdle>): AIC for Hurdle Demand Model
BIC(<beezdemand_hurdle>): BIC for Hurdle Demand Model
logLik(<beezdemand_hurdle>): Extract Log-Likelihood from Hurdle Demand Model
get_subject_pars(): Get Subject-Specific Parameters
extract_coefficients(): Extract All Coefficient Types from Cross-Price Demand Models

Prediction

Methods for generating predictions from fitted models.

predict(<beezdemand_fixed>): Predict Method for beezdemand_fixed
predict(<beezdemand_hurdle>): Predict Method for Hurdle Demand Models
predict(<beezdemand_nlme>): Predict Method for beezdemand_nlme Objects
predict(<cp_model_lm>): Predict method for cp_model_lm objects.
predict(<cp_model_lmer>): Predict from a Mixed-Effects Cross-Price Demand Model
predict(<cp_model_nls>): Predict from a Cross-Price Demand Model (Nonlinear)

Post-Hoc Analysis

Functions for post-hoc comparisons and inference.

get_demand_param_emms(): Get Estimated Marginal Means for Demand Parameters
get_demand_comparisons(): Get Pairwise Comparisons for Demand Parameters
get_demand_param_trends(): Get Trends (Slopes) of Demand Parameters with respect to Continuous Covariates
get_observed_demand_param_emms(): Get Estimated Marginal Means for Observed Factor Combinations
get_individual_coefficients(): Calculate Individual-Level Predicted Coefficients from beezdemand_nlme Model
cp_posthoc_slopes(): Run pairwise slope comparisons for cross-price demand model
cp_posthoc_intercepts(): Run pairwise intercept comparisons for cross-price demand model

Derived Metrics

Functions for computing demand-derived metrics like Pmax and Omax.

calc_omax_pmax(): Calculate Omax and Pmax for Demand Curves
calc_observed_pmax_omax(): Calculate Observed Pmax/Omax Grouped by ID
calc_group_metrics(): Calculate Group-Level Demand Metrics
beezdemand_calc_pmax_omax(): Calculate Pmax and Omax with Method Reporting and Parameter-Space Safety
beezdemand_calc_pmax_omax_vec(): Calculate Pmax/Omax for Multiple Subjects
get_empirical_measures(): Calculate Empirical Demand Measures
get_descriptive_summary(): Calculate Descriptive Statistics by Price
get_k(): Calculate K Scaling Parameter for Demand Curve Fitting
GetAnalyticPmax(): Get pmax
GetAnalyticPmaxFallback(): Analytic Pmax Fallback
GetEmpirical(): GetEmpirical
GetDescriptives(): Get Purchase Task Descriptive Summary
GetK(): Get K
GetSharedK(): Get Shared K
calculate_amplitude_persistence(): Calculate Amplitude and Persistence

Model Comparison

Functions for comparing models.

compare_hurdle_models(): Compare Nested Hurdle Demand Models
compare_models(): Compare Demand Models
check_demand_model(): Check Demand Model Diagnostics
anova(<beezdemand_hurdle>): ANOVA Method for Hurdle Demand Models
anova(<beezdemand_nlme>): ANOVA Method for NLME Demand Models
ExtraF(): ExtraF

Visualization

Plotting functions and themes.

print(<beezdemand_descriptive>) summary(<beezdemand_descriptive>) plot(<beezdemand_descriptive>): S3 Methods for beezdemand_descriptive Objects
print(<beezdemand_empirical>) summary(<beezdemand_empirical>) plot(<beezdemand_empirical>): S3 Methods for beezdemand_empirical Objects
plot-theme: beezdemand Plot Theme and Color Palette
plot(<beezdemand_fixed>): Plot Method for beezdemand_fixed
plot(<beezdemand_hurdle>): Plot Demand Curves from Hurdle Demand Model
plot(<beezdemand_nlme>): Plot Method for beezdemand_nlme Objects
plot(<cp_model_lm>): Plot Method for Linear Cross-Price Demand Models
plot(<cp_model_lmer>): Plot Method for Mixed-Effects Cross-Price Demand Models
plot(<cp_model_nls>): Plot a Cross-Price Demand Model (Nonlinear)
plot_qq(): Plot Random Effects Q-Q
plot_residuals(): Plot Residual Diagnostics
plot_subject(): Plot Demand Curve for a Single Subject
PlotCurve(): Plot Curve
PlotCurves(): Plot Curves
theme_beezdemand(): beezdemand Plot Theme
theme_apa(): APA Theme
palette_beezdemand(): beezdemand Color Palette
scale_color_beezdemand(): beezdemand Color Scale (Discrete)
scale_fill_beezdemand(): beezdemand Fill Scale (Discrete)

Transformations

Data transformation utilities.

ll4(): Log-Logistic Transformation (LL4-like)
ll4_inv(): Inverse Log-Logistic Transformation (Inverse LL4-like)
scale_ll4(): Create an LL4-like Scale for ggplot2 Axes
pseudo_ll4_trans(): Create a Pseudo-Log LL4 Transformation Object for ggplot2
lambertW(): Lambert W

Simulation

Functions for simulating demand data.

simulate_hurdle_data(): Simulate Data from Two-Part Mixed Effects Hurdle Demand Model
SimulateDemand(): Simulate Demand Data
run_hurdle_monte_carlo(): Run Monte Carlo Simulation Study for Hurdle Demand Model
print_mc_summary(): Print Monte Carlo Simulation Results
GetValsForSim(): Get Values for SimulateDemand

Summary Methods

Summary functions for parameter exploration.

get_hurdle_param_summary(): Get Hurdle Model Parameter Summary
print(<beezdemand_descriptive>) summary(<beezdemand_descriptive>) plot(<beezdemand_descriptive>): S3 Methods for beezdemand_descriptive Objects
print(<beezdemand_empirical>) summary(<beezdemand_empirical>) plot(<beezdemand_empirical>): S3 Methods for beezdemand_empirical Objects
summary(<beezdemand_fixed>): Summary Method for beezdemand_fixed
summary(<beezdemand_hurdle>): Summarize a Hurdle Demand Model Fit
summary(<beezdemand_nlme>): Summary method for beezdemand_nlme
summary(<beezdemand_systematicity>): Summary Method for beezdemand_systematicity
summary(<cp_model_lm>): Summary method for cp_model_lm objects.
summary(<cp_model_lmer>): Summary method for cp_model_lmer objects.
summary(<cp_model_nls>): Summarize a Cross-Price Demand Model (Nonlinear)
summary(<cp_unsystematic>): Summarize Cross-Price Unsystematic Data Check Results
print(<anova.beezdemand_hurdle>): Print Method for ANOVA Comparisons
print(<beezdemand_comparison>): Print method for beezdemand_comparison objects
print(<beezdemand_diagnostics>): Print Method for Model Diagnostics
print(<beezdemand_fixed>): Print Method for beezdemand_fixed
print(<beezdemand_hurdle>): Print Method for Hurdle Demand Model
print(<beezdemand_model_comparison>): Print Method for Model Comparison
print(<beezdemand_nlme>): Print Method for beezdemand_nlme Objects
print(<beezdemand_summary>): Print Method for beezdemand Summary Objects
print(<beezdemand_systematicity>): Print Method for beezdemand_systematicity
print(<cp_posthoc>): Print method for cp_posthoc objects
print(<summary.beezdemand_fixed>): Print Method for summary.beezdemand_fixed
print(<summary.beezdemand_hurdle>): Print Summary of Hurdle Demand Model
print(<summary.beezdemand_nlme>): Print method for summary.beezdemand_nlme
print(<summary.beezdemand_systematicity>): Print Method for summary.beezdemand_systematicity
print(<summary.cp_model_lm>): Print method for summary.cp_model_lm objects.
print(<summary.cp_model_lmer>): Print method for summary.cp_model_lmer objects.
print(<summary.cp_model_nls>): Print method for summary.cp_model_nls objects
print(<summary.cp_unsystematic>): Print Method for Cross-Price Unsystematic Summary
print_mc_summary(): Print Monte Carlo Simulation Results

Validation & Data Checking

Functions for validating data inputs.

validate_demand_data(): Validate and Prepare Demand Data
validate_hurdle_data(): Validate Hurdle Demand Data
validate_cp_data(): Validate and Filter Cross-Price Demand Data
validate_collapse_levels(): Validate Collapse Levels Structure
validate_param_scale(): Validate Parameter Scale
new_beezdemand_systematicity(): Create a beezdemand_systematicity Object

Utilities & Helpers

Internal utility functions and helpers.

annotation_logticks2(): annotation_logticks2
build_fixed_rhs(): Build Fixed-Effects RHS Formula String
collapse_factor_levels(): Collapse Factor Levels for a Specific Parameter
format_param_name(): Format Parameter Name with Scale Prefix
get_canonical_metric(): Get Canonical Derived Metric Name
get_canonical_param(): Get Canonical Parameter Name
get_equation_spec(): Get Equation Specification
get_legacy_mapping(): Legacy to Canonical Mapping Table
get_pooled_nls_starts(): Get Starting Values from a Pooled NLS Model (Internal Helper)
calc_omax_pmax_vec(): Calculate Omax and Pmax for Multiple Subjects

Documentation Topics

Documentation-only pages that group related methods.

cp: Example cross‐price dataset
fixed-demand: Fixed-Effect Demand Curve Fitting
param-registry: Parameter Naming Registry for beezdemand
plot-theme: beezdemand Plot Theme and Color Palette
pmax-omax-engine: Pmax/Omax Engine
systematic-wrappers: Systematicity Check Wrappers
coef(<cp_model_nls>) coef(<cp_model_lm>) coef(<cp_model_lmer>): Extract Coefficients from Cross-Price Demand Models
reexports tidy glance augment: Objects exported from other packages

Example Datasets

Built-in datasets for examples and testing.

apt: Example alcohol purchase task data
apt_full: Full alcohol purchase task dataset
ko: Example nonhuman demand data with drug and dose
etm: Example Experimental Tobacco Marketplace data
cannabisCigarettes: Cannabis/cigarette cross-price responses
lowNicClean: Low-nicotine cigarette purchase task
ongoingETM: Experimental Tobacco Marketplace (ETM) data

Deprecated

Functions that have been deprecated and will be removed in future versions.

pull() deprecated: Pull