R: Tools for Applying Catalytic Priors in Statistical Modeling

# Tools for Applying Catalytic Priors in Statistical Modeling

## Documentation for package ‘catalytic’ version 0.1.0

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

## Help Pages

cat_cox | Catalytic Cox Proportional Hazards Model (COX) Fitting Function with Fixed Tau
cat_cox_bayes | Bayesian Estimation for Catalytic Cox Proportional-Hazards Model (COX) with Fixed tau
cat_cox_bayes_joint | Bayesian Estimation for Catalytic Cox Proportional-Hazards Model (COX) with adaptive tau
cat_cox_initialization | Initialization for Catalytic Cox proportional hazards model (COX)
cat_cox_tune | Catalytic Cox Proportional-Hazards Model (COX) Fitting Function by Tuning tau from a Sequence of tau Values
cat_glm | Catalytic Generalized Linear Models (GLMs) Fitting Function with Fixed Tau
cat_glm_bayes | Bayesian Estimation for Catalytic Generalized Linear Models (GLMs) with Fixed tau
cat_glm_bayes_joint | Bayesian Estimation for Catalytic Generalized Linear Models (GLMs) with adaptive tau
cat_glm_bayes_joint_gibbs | Bayesian Estimation with Gibbs Sampling for Catalytic Generalized Linear Models (GLMs) Binomial Family for Coefficients and tau
cat_glm_initialization | Initialization for Catalytic Generalized Linear Models (GLMs)
cat_glm_tune | Catalytic Generalized Linear Models (GLMs) Fitting Function by Tuning tau from a Sequence of tau Values
cat_lmm | Catalytic Linear Mixed Model (LMM) Fitting Function with fixed tau
cat_lmm_initialization | Initialization for Catalytic Linear Mixed Model (LMM)
cat_lmm_tune | Catalytic Linear Mixed Model (LMM) Fitting Function by Tuning tau from a Sequence of tau Values
cross_validation | Perform Cross-Validation for Model Estimation
cross_validation_cox | Perform Cross-Validation for Catalytic Cox Proportional-Hazards Model (COX) to Select Optimal tau
cross_validation_lmm | Perform Cross-Validation for Catalytic Linear Mixed Model (LMM) to Select Optimal tau
extract_coefs | Extract and Format Model Coefficients
extract_dim | Extract Dimension Information from Model Initialization
extract_stan_summary | Extract and Format Summary of Stan Model Results
extract_tau_seq | Extract and Format Sequence of Tau Values
get_adjusted_cat_init | Adjusted Cat Initialization
get_cox_gradient | Compute the Gradient for Cox Proportional Hazards Model
get_cox_hessian | Compute the Hessian Matrix for Cox Proportional Hazards Model
get_cox_kappa | Estimate the kappa value for the synthetic Cox proportional hazards model
get_cox_partial_likelihood | Compute the Partial Likelihood for the Cox Proportional Hazards Model
get_cox_qr_solve | Solve Linear System using QR Decomposition
get_cox_risk_and_failure_sets | Calculate Risk and Failure Sets for Cox Proportional Hazards Model
get_cox_risk_set_idx | Identify the risk set indices for Cox proportional hazards model
get_cox_syn_gradient | Compute the gradient of the synthetic Cox proportional hazards model
get_cox_syn_hessian | Compute the Synthetic Hessian Matrix for Cox Proportional Hazards Model
get_discrepancy | Compute Discrepancy Measures
get_formula_lhs | Extract Left-Hand Side of Formula as String
get_formula_rhs | Extract the Right-Hand Side of a Formula
get_formula_string | Convert Formula to String
get_glm_custom_var | Get Custom Variance for Generalized Linear Model (GLM)
get_glm_diag_approx_cov | Compute Diagonal Approximate Covariance Matrix
get_glm_family_string | Retrieve GLM Family Name or Name with Link Function
get_glm_lambda | Compute Lambda Based on Discrepancy Method
get_glm_log_density | Compute Log Density Based on GLM Family
get_glm_log_density_grad | Compute Gradient of Log Density for GLM Families
get_glm_mean | Compute Mean Based on GLM Family
get_glm_sample_data | Generate Sample Data for GLM
get_hmc_mcmc_result | Run Hamiltonian Monte Carlo to Get MCMC Sample Result
get_linear_predictor | Compute Linear Predictor
get_resampled_df | Resampling Methods for Data Processing
get_standardized_data | Standardize Data
get_stan_model | Generate Stan Model Based on Specified Parameters
hmc_neal_2010 | Hamiltonian Monte Carlo (HMC) Implementation
is.continuous | Check if a Variable is Continuous
mallowian_estimate | Perform Mallowian Estimate for Model Risk (Only Applicable for Gaussian Family)
parametric_bootstrap | Perform Parametric Bootstrap for Model Risk Estimation
plot.cat_tune | Plot Likelihood or Risk Estimate vs. Tau for Tuning Model
predict.cat_cox | Predict Linear Predictor for New Data Using a Fitted Cox Model
predict.cat_glm | Predict Outcome for New Data Using a Fitted GLM Model
predict.cat_lmm | Predict Linear Predictor for New Data Using a Fitted Linear Mixed Model
print.cat | Print Method for 'cat' Object
print.cat_bayes | Print Summary of 'cat_bayes' Model
print.cat_gibbs | Print Summary of 'cat_gibbs' Model
print.cat_initialization | Print Summary for Catalytic Initialization Model
print.cat_tune | Print Method for 'cat_tune' Object
print_df_head_tail | Print Data Frame with Head and Tail Rows
print_glm_bayes_joint_binomial_suggestion | Generate Suggestions for Bayesian Joint Binomial GLM Parameter Estimation
steinian_estimate | Perform Steinian Estimate for Model Risk (Only Applicable for Binomial Family)
swim | Simulated SWIM Dataset with Binary Response
traceplot | Traceplot for Bayesian Model Sampling
traceplot.cat_bayes | Traceplot for Bayesian Sampling Model
traceplot.cat_gibbs | Traceplot for Gibbs Sampling Model
update_lmm_variance | Calculates the log-likelihood for linear mixed models (LMMs) by combining observed and synthetic log-likelihoods based on the variance parameters.
validate_cox_initialization_input | Validate Inputs for Catalytic Cox proportional hazards model (COX) Initialization
validate_cox_input | Validate Inputs for Catalytic Cox Model
validate_glm_initialization_input | Validate Inputs for Catalytic Generalized Linear Models (GLMs) Initialization
validate_glm_input | Validate Inputs for Catalytic Generalized Linear Models (GLMs)
validate_lmm_initialization_input | Validate Inputs for Catalytic Linear Mixed Model (LMM) Initialization
validate_lmm_input | Validate Inputs for Catalytic Linear Mixed Model (LMM)
validate_positive | Validate Positive or Non-negative Parameter