Learn R Programming

qbrms (version 1.0.1)

Quick Bayesian Regression Models Using 'INLA' with 'brms' Syntax

Description

Provides a 'brms'-like interface for fitting Bayesian regression models using 'INLA' (Integrated Nested Laplace Approximations) and 'TMB' (Template Model Builder). The package offers faster model fitting while maintaining familiar 'brms' syntax and output formats. Supports fixed and mixed effects models, multiple probability distributions, conditional effects plots, and posterior predictive checks with summary methods compatible with 'brms'. 'TMB' integration provides fast ordinal regression capabilities. Implements methods adapted from 'emmeans' for marginal means estimation and 'bayestestR' for Bayesian inference assessment. Methods are based on Rue et al. (2009) , Kristensen et al. (2016) , Lenth (2016) , Bürkner (2017) , Makowski et al. (2019) , and Kruschke (2014, ISBN:9780124058880).

Copy Link

Version

Install

install.packages('qbrms')

Version

1.0.1

License

MIT + file LICENSE

Issues

Pull Requests

Stars

Forks

Maintainer

Tony Myers

Last Published

December 10th, 2025

Functions in qbrms (1.0.1)

check_convergence

Quick model diagnostics
coef.tmb_ordinal_qbrms_fit

Coefficients Method for TMB Ordinal Fits
circular_normal

Circular Normal Family for Directional Data
coef.qbrms_multinomial_fit

Coefficients for multinomial qbrms fits
c.qbrms_prior_spec

Combine Multiple Prior Specifications
binomial

Binomial Family
coef.qbrms_fit

Extract Coefficients from qbrms Models
clean_coefficient_names

Clean up malformed coefficient names from mixed effects models
cauchy

Specify Cauchy Prior Distribution
build_html_table_styled

Build HTML Table with Enhanced Styling
conditional_effects.tmb_ordinal_qbrms_fit

Conditional Effects for TMB Ordinal Models
conditional_effects.qbrms_fit

Conditional effects for qbrms Gaussian models
conditional_effects_slices

Discrete-slice conditional effects (brms-style) for qbrms
convert_family_to_inla

Convert Family Object to INLA-Compatible Specification
create_dummy_data_for_priors

Create Dummy Data for Prior Predictive Checks
diagnose_model

Automated Model Diagnostics and Recommendations
default_priors

Default Priors for qbrms Models
compare_significance

Compare Significance Across Multiple Models
compare_models

Compare qbrms models
cumulative

Cumulative Family for Ordinal Regression
create_dummy_data

Create Dummy Data for Testing
create_fixed_effects_summary

Create Fixed Effects Summary Table
density_plot

Density Plot for qbrms Models
diagnose_binomial_mixed

Diagnose Binomial Mixed Effects Models
create_prior_object

Create Prior-Only Object for pp_check
conditional_effects

Conditional effects (generic)
compute_adaptive_threshold_priors

Compute Data-Driven Threshold Priors
create_ordinal_qbrms_result

Create qbrms-Compatible Result Object
.add_comprehensive_diagnostics

Add comprehensive post-fitting diagnostics
.apply_threshold_constraints

Apply threshold constraints manually (fallback)
.assess_group_problems

Assess group-specific problems
.apply_single_prior_spec_standalone

Apply Single Prior Specification
.apply_inverse_link

Apply inverse link function
.check_convergence

Check Convergence
.bayes_R2_brms_style

Compute Bayesian R-squared exactly as in brms
.add_reference_distributions

Add Reference Distributions
.analyse_group_structure

Analyse grouping structure
.augment_data_for_stability

Data augmentation for model stability
.augment_data_intelligent

Intelligent data augmentation
.check_posterior

Check Posterior Distribution
.check_global_separation

Check for global separation issues
.choose_fitting_strategy

Choose optimal fitting strategy
.compute_improved_threshold_priors

Improved Threshold Prior Computation - ENHANCED VERSION
.check_model_fit

Check Model Fit
create_quantile_fit

Utility operator
.diagnose_comprehensive

Comprehensive diagnostic assessment
.compute_threshold_se_delta_method

Compute Threshold Standard Errors Using Delta Method - NEW FUNCTION
.check_influential_observations

Check for Influential Observations
.compute_robust_vcov

Compute Robust Variance-Covariance Matrix - CORRECTED VERSION
.create_balanced_augmentation

Create balanced augmented observations
.export_as_markdown

Export as Markdown
.diagnose_binomial_issues

Internal function to diagnose binomial issues
.determine_xlim

Determine X-axis Limits
.convert_to_inla_formula

Convert lme4-style formula to INLA format
.fit_minimal_strategy

Minimal strategy
.extract_group_variable

Extract group variable from formula
.export_as_text

Export as Plain Text
.drop_random_effects

Drop random-effect terms from a formula
.format_prior_label

Format Prior Label
.generate_emmeans_predictions_simple

Simplified prediction function for emmeans (avoids dimension issues)
.create_density_base_plot

Create Base Density Plot
.fit_ridge_fallback

Ridge regression fallback
.export_as_json

Export as JSON
.generate_response_from_family

Generate Response from Family Distribution
.evaluate_prior_density

Evaluate Prior Density
.fit_aggressive_strategy

Aggressive strategy
.fit_enhanced_strategy

Enhanced strategy
.export_as_r_script

Export as R Script
.create_ordinal_routing_object

Create Ordinal Routing Object
.drop_random_effects_for_r2

Remove random effects from formula for design matrix creation
.infer_recommended_families

Infer recommended families from a response vector
.extract_prior_specs_standalone

Extract Prior Specifications (Standalone Version)
.mb_get_response

Get Response Variable
.qbrms__generate_spaghetti_draws_corrected

Generate spaghetti draws
.estimate_random_effects_variance_from_data_corrected

Estimate random effects variance from data - CORRECTED
.mb_present_summary

Present Summary
.extract_parameter_densities

Extract Parameter Distribution Densities
.mb_characterise_response

Characterise Response Variable
.qbrms__remove_random_effects

Remove random effects from formula
.mb_create_family_object

Create Family Object
.mb_build_formula

Build Formula
.check_residuals

Check Residuals
.generate_posterior_epred_corrected

Generate posterior expected predicted values - CORRECTED for mixed models
.fit_with_strategy

Fit model using specified strategy
.fit_with_inla_enhanced

Core INLA fitting function
emmeans

Estimated marginal means (compatibility wrapper)
.create_prior_only_plot

Create Prior-Only Plot
.sample_from_prior

Sample from Prior Distribution
.sample_from_prior_safe

Safe Prior Sampling
.mb_select_family

Let User Select Family
.check_sparse_outcomes

Check for sparse outcomes
.generate_prior_only_samples

Generate Prior-Only Samples
drop_random_effects

Drop Random Effects from Formula
.qbrms__compute_ols_covariance

Compute OLS covariance matrix as fallback
.summarise_bayes_r2

Summarise Bayesian R-squared values
.visualise_prior_comparison

Visualise Prior Comparison
.mb_generate_code

Generate Model Code
.qbrms__enhance_covariance_matrix

Enhance covariance matrix to ensure proper correlations
.mb_suggest_families

Suggest Appropriate Families
gamma

Gamma Distribution (Prior or Family)
families

Family Conversion and Utilities for qbrms Package
.validate_qbrmb_inputs

Validate qbrmb inputs
extract_routing_info

Extract Routing Information from Family Specification
exponential

Exponential Distribution (Prior or Family)
extract_model_info

Extract Model Information for HTML Table
gaussian

Gaussian Family
.qbrms__compute_geometric_covariance

Compute geometric covariance from design matrix properties
fit_ordinal_tmb_model

Enhanced TMB Model Fitting with Better Error Handling - CORRECTED VERSION
.qbrms__compute_leverage_uncertainty

Compute leverage-aware confidence intervals
fit_ordinal_model

Fit ordinal model with fallbacks
gev

Generalized Extreme Value Family
extract_model_metrics

Extract Model Metrics
get_random_effects_sd_summary

Get Random Effects Standard Deviation Summary
.print_diagnostic_summary

Print Diagnostic Summary
fit_model_robust_fixed

Robust model fitting with better error handling (FIXED - no recursion)
.mb_get_data

Get Data from User
.prepare_random_effects_corrected

Prepare random effects structure - CORRECTED
.mb_get_predictors

Get Predictor Variables
generate_table_css

Generate CSS for different table styles
fit_multinomial_model

Fit Multinomial Model using INLA or fallback
iid

IID Random Effects
neg_binomial

Negative Binomial Family
.remove_random_effects

Remove random effects from formula
hurdle_families

Hurdle Families for Two-Part Models
family_supports_quantile

Check if Family Supports Quantile Regression
format_bf

Format Bayes Factor for Display
format_digits

Format numerical values to specified digits
generate_prior_predictions_simple

Generate Prior Predictions (Simple)
fit_fallback_model

Fallback model fitting for edge cases
get_default_prior

Get Default Prior for Parameter Class
export_model

Export Model Specification
extract_family_name

Extract Family Name from INLA Family Specification
.sample_from_inla_random_effects

Sample from INLA random effects posteriors - CORRECTED
fitted.qbrms_fit

Extract fitted values from qbrms models
fit_mixed_effects_model

Fit Mixed Effects Model using INLA with proper formula conversion
handle_missing_data

Handle Missing Data
fit_fixed_effects_model

Fit Fixed Effects Model (standalone to avoid recursion)
hdi

Highest Density Interval (HDI)
negbinomial

Negative Binomial Family (Alias)
print.qbrms_fit

Print Method for qbrms_fit Objects
plot.qbrms_diagnostics

Plot Method for Diagnostics
print.qbrms_kfold

Print Method for qbrms_kfold Objects
plot.qbrms_conditional_effects

Plot conditional effects for qbrms models
.extract_random_effects_variance_corrected

Extract random effects variance - CORRECTED
.extract_inla_marginals_with_random_effects

Extract INLA marginals with random effects - CORRECTED
.extract_inla_fitted_with_random_effects

Extract INLA fitted values that include random effects - CORRECTED
.extract_response_densities

Extract Response Distribution Densities
.create_synthetic_data

Create Synthetic Data for Prior Checks
gen_student_t

Generalized t Family
fitted.tmb_ordinal_qbrms_fit

Fitted Values Method for TMB Ordinal Fits
import_model

Import Model Specification from JSON
print.qbrms_prior_list

Print Prior List Objects
generate_posterior_predictive_samples

Generate posterior predictive samples
normal

Specify Normal Prior Distribution
is_ordinal

Check if family is ordinal
model_lab_addin

qbrms Model Lab (RStudio Add-in)
prior_code

Format priors as qbrms prior() code
model_fitting

Model Fitting Functions for qbrms Package
p_direction

Probability of Direction (pd)
print.qbrms_prior_spec

Print Prior Specification Objects
ordinal_plots

Ordinal Plots and Posterior Predictive Checks
format_duration

Format Duration
model_workflow_addin

Launch Guided Bayesian Workflow (RStudio Add-in)
format_number

Format Number for Display
print.qbrmsformula

Print method for qbrms formulas
print.qbrms_prior_code

Print method for qbrms_prior_code objects
multinomial

Multinomial Family
plot.qbrms_p_significance

Plot Method for Enhanced p_significance
plot_parameters

Plot Parameters with Prior/Posterior Comparison
poisson_trick_multinomial

Poisson Trick for Multinomial
list_extended_families

List Available Extended Families
print.qbrms_prior_build

Print method for qbrms_prior_build objects
poisson

Poisson Family
parse_formula_components

Parse Formula Components
generate_prior_predictive_samples

Generate prior predictive samples (compat wrapper) - FIXED
null-coalesce

Null Coalescing Operator
parse_ordinal_formula

Parse Ordinal Formula Components
print.summary.qbrms_fit

Print Method for summary.qbrms_fit Objects
qbrms-globals

Internal globals for qbrms
quick_density_comparison

Quick Density Comparison
qbrms_set_verbosity

Set qbrms verbosity for the current session
prior_pp_diagnostics

Prior predictive diagnostics and sensibility report
qbrms-imports

Internal import directives for qbrms
lognormal

Lognormal Family Constructor
.generate_prior_predictive_samples

Generate Prior Predictive Samples
qbrmO

Quick Bayesian Ordinal Regression Models with Adaptive Centering
safe_model_matrix

Safe construction of model matrices
rope_analysis

ROPE analysis
model_builder

Interactive Model Builder for qbrms (console)
prepare_ordinal_tmb_data

Prepare Data for TMB Ordinal Model
pp_check_prior

Prior Predictive Checks Without Data
loo_compare

Compare models by LOO (default) or WAIC
print.qbrms_prior_diagnostics

Print method for qbrms_prior_diagnostics objects
uniform

Specify Uniform Prior Distribution
qbrms_emmeans

Estimated Marginal Means for qbrms models
prior_build_from_beliefs

Prior Build from Beliefs
print.qbrms_prior_dist

Print Prior Distribution Objects
qbrms_binomial_regularised

Fixed Regularised Binomial Mixed Effects Fitting
sanitize_formula

Sanitize Formula (Distributional Safety Catch)
setup_ordinal_tmb

Set Up TMB Model Object
qbrms_ordinal_binary

Ordinal regression via binary decomposition (fallback)
qbrmb

Enhanced binomial mixed-effects modelling
qbrms_fit_log

Get captured fit log from a qbrms object (if available)
prior_checks

Prior Predictive Checks and Density Plotting
tab_model

Create HTML Table for qbrms Models with Enhanced Styling
validate_family_data

Validate Family-Specific Data Constraints
print.qbrmb_fit

Print a qbrmb model fit
.mb_get_priors

Get Prior Specifications
.generate_random_effects_corrected

Generate random effects for one posterior draw - CORRECTED
print.qbrms_diagnostics

Print Method for Diagnostics
print.qbrms_multinomial_fit

Print method for multinomial qbrms fits
print.qbrms_p_significance

Print Method for Enhanced p_significance
prior_to_posterior_workflow

Complete Prior-to-Posterior Workflow
prior_predictive_check

Create Prior Predictive Distribution Plot
prior_pp_summary

A convenience wrapper mirroring pp_check's show_observed flag
priors

Prior Distribution Specifications
.mb_get_random_effects

Get Random Effects Structure
test_corrected_bayes_R2

Test the corrected implementation with a mixed-effects example
family_info

Get Family Documentation
extract_ordinal_info

Extract Ordinal Information from Family
.regularize_hessian

Regularize Hessian Matrix for Numerical Stability
.reconstruct_predictions_corrected

Reconstruct predictions manually - CORRECTED for mixed models
.parse_prior_string

Parse Prior String
.parse_prior_specification

Parse Prior Specification
extract_ordinal_parameters

Extract Parameter Estimates and Standard Errors - CORRECTED VERSION
family_conversion

Family conversion utilities for qbrms package
view_table

Display HTML Table in Viewer
visualise_prior

Visualise Prior Distributions
format_numeric_df

Format data frame with numerical columns
kfold_cv

K-fold cross-validation for qbrms models (ordinal and standard families)
p_significance

Probability of Practical Significance (Enhanced bayestestR-style)
laplace

Laplace (Double Exponential) Family
format_percentage

Format Percentage for Display
get_enhanced_inla_control

Get Enhanced INLA Control Settings for Family-Specific Stability
get_predictor_variables

Get Predictor Variables from Formula
qbrmb_aggressive

Aggressively regularised binomial mixed-effects model
parse_brms_formula

Parse brms Formula Objects
random_walk_families

Random Walk Families
zero_inflated_poisson

Zero-Inflated Poisson Family
requires_routing

Check if Family Requires Routing to Specialist Implementation
pp_check

Posterior and prior predictive checks
pp_check.tmb_ordinal_qbrms_fit

Posterior predictive checks for TMB ordinal models
summary.qbrmb_fit

Summary Method for qbrmb_fit Objects
vcov.tmb_ordinal_qbrms_fit

Variance-Covariance Matrix Method for TMB Ordinal Fits
vcov.qbrms_fit

Extract Variance-Covariance Matrix from qbrms Models
student_t

Student's t Family for Robust Regression
qbrmb_regularised

Regularised binomial mixed-effects (enhanced strategy)
skew_normal

Skew Normal Family
simplex

Simplex Family for Compositional Data
qbrms-model-criteria

Model comparison criteria for qbrms models
qbrms-package

qbrms: Quick Bayesian Regression Models using INLA
prior

Specify Prior for Model Parameters
print.qbrms_model_spec

Print Method for qbrms_model_spec
print.qbrms_loo_compare

Print Method for qbrms_loo_compare Objects
print.tmb_ordinal_qbrms_fit

Print Method for TMB Ordinal Fits
qbrms

Quick Bayesian Regression Models with Automatic Routing
qbrms_bayesian_analysis

Bayesian Analysis Functions (qbrms)
summary.qbrms_fit

Summary Method for qbrms_fit Objects
qbrm

Alias for qbrms()
process_ordinal_priors_adaptive

Enhanced Prior Processing with Adaptive Centering - CORRECTED VERSION
summary.qbrms_p_significance

Summary Method for Enhanced p_significance
summary.tmb_ordinal_qbrms_fit

Summary Method for TMB Ordinal Fits
residuals.qbrms_fit

Extract residuals from qbrms models
requires_special_handling

Check if Family Requires Special Handling
validate_model_data

Validate data before model fitting
summary.qbrms_multinomial_fit

Summary method for multinomial qbrms fits
weibull

Weibull Survival Family
validate_family_quantile

Validate Family Quantile Combination
zero_inflated_negbinomial

Zero-Inflated Negative Binomial Family
additional_families

Additional Statistical Families for qbrms
asymmetric_laplace

Asymmetric Laplace for Quantile Regression
bf

Create a Bayesian Formula
bayes_R2

Bayesian R-squared for qbrms Models
beta_variants

Alternative Beta Parameterizations
beta_binomial

Beta Binomial Family for Overdispersed Binary Data
Gamma_family

Gamma family (GLM-style)
beta_prior

Specify Beta Prior Distribution
bayesfactor

Bayesian Hypothesis Testing (very simple approximations)
Beta

Beta Family Constructor (Capital B)