Package index • degen

Model Specification

Define models via their log-likelihood functions

model_spec(): Create a model specification
is_model_spec(): Test if object is a model_spec
par_names(): Get parameter names
par_bounds(): Get parameter bounds
n_par(): Get number of parameters
loglik(): Evaluate log-likelihood
validate_loglik(): Validate a log-likelihood function
diagnose_model(): Diagnose model specification issues
check_gradient(): Check numerical gradient against analytical

Distribution Helpers

Pre-built model specifications for common distributions

model_spec_normal(): Create model_spec for Normal distribution
model_spec_exponential(): Create model_spec for Exponential distribution
model_spec_gamma(): Create model_spec for Gamma distribution
model_spec_poisson(): Create model_spec for Poisson distribution
model_spec_binomial(): Create model_spec for Binomial distribution
model_spec_beta(): Create model_spec for Beta distribution
model_spec_lognormal(): Create model_spec for Log-normal distribution
model_spec_weibull(): Create model_spec for Weibull distribution
model_spec_negbinom(): Create model_spec for Negative Binomial distribution
model_spec_uniform(): Create model_spec for Uniform distribution

Model Comparison

Compare likelihood surfaces between models

equivalence_pair(): Create an equivalence pair for model comparison
is_equivalence_pair(): Test if object is an equivalence_pair
spec_a() spec_b(): Extract model specification from pair
par_dims(): Get parameter dimensions for both models
same_par_count(): Check if models have same parameter count
compare_surfaces(): Compare likelihood surfaces between two models
is_surface_comparison(): Test if object is a surface_comparison
debug_comparison(): Debug comparison trace

Equivalence Classes

Group multiple models by equivalence

equivalence_classes(): Find equivalence classes among multiple models
is_equiv_classes(): Test if object is an equiv_classes
n_classes(): Get number of equivalence classes
class_members(): Get members of an equivalence class
are_equivalent(): Check if two models are equivalent
equivalence_matrix(): Create equivalence matrix visualization

Batch Comparison

Compare multiple models systematically

compare_all_pairs(): Compare all pairs of models
find_equivalent_to(): Find all models equivalent to a reference

Fisher Information

Compute and analyze Fisher information matrices

fisher_information(): Compute Fisher information matrix
is_fisher_info(): Test if object is a fisher_info
info_eigenvalues(): Extract eigenvalues from Fisher information
info_condition(): Get condition number of Fisher information
info_rank(): Get numerical rank of Fisher information
null_directions(): Find directions of non-identifiability
fisher_analytical(): Compute analytical Fisher information
symbolic_fisher(): Symbolic Fisher information

Identifiability

Diagnose identifiability issues within a model

identifiability_check(): Check model identifiability
is_identifiability_result(): Test if object is an identifiability_result
profile_likelihood(): Compute profile likelihood for one parameter
profile_ci(): Compute profile likelihood confidence intervals
detect_linear_reparam(): Detect linear reparameterization
check_exact_equivalence(): Check for exact parameter equivalence

Model Fitting

Fit models and extract specifications from fitted objects

fit_model(): Fit a model specification via MLE
model_spec_from_fit(): Extract model_spec from fitted R objects
model_vcov(): Compute variance-covariance from Fisher information
coef(<fitted_model_spec>): Extract coefficients from fitted model_spec
vcov(<fitted_model_spec>): Extract variance-covariance matrix
confint(<model_spec>): S3 method for confint

Simulation

Simulate data from model specifications

add_simulator(): Add simulation function to model_spec
can_simulate(): Check if model_spec can simulate
simulate(<model_spec>): Simulate data from a model specification

Sensitivity Analysis

Test robustness of equivalence conclusions

sensitivity_analysis(): Sensitivity analysis for equivalence testing
bootstrap_equivalence(): Bootstrap test for equivalence
cross_validate_equivalence(): Cross-validation test for equivalence

Bayesian Methods

Posterior-based model comparison

compare_posteriors(): Compare posterior distributions
prior_sensitivity(): Prior sensitivity analysis
extract_samples(): Extract posterior samples from fitted objects

Visualization

Plot results and diagnostics

plot_likelihood_surface(): Plot likelihood surface
plot_profile_likelihood(): Plot profile likelihood for a parameter
plot(<equiv_classes>): Plot equivalence classes
plot(<fisher_info>): Plot Fisher information diagnostics
plot(<identifiability_result>): Plot identifiability diagnostics
plot(<surface_comparison>): Plot surface comparison results

Export and Conversion

Export results for reporting

export_results(): Export results to file
to_latex(): Format results as LaTeX table
as.data.frame(<equiv_classes>): Convert equiv_classes to data frame
as.data.frame(<fisher_info>): Convert fisher_info to data frame
as.data.frame(<identifiability_result>): Convert identifiability_result to data frame
as.data.frame(<surface_comparison>): Convert surface_comparison to data frame

Parallel Processing

Enable parallel computation

setup_cluster(): Set up parallel cluster
stop_cluster(): Stop parallel cluster

Example Datasets

Bundled datasets for examples and testing

ecological_models: Ecological population models
equivalent_models: Equivalent model pairs
mixture_model: Mixture model with label switching
nonidentifiable_example: Non-identifiable model example