Package index • CPN

All functions

AIC(<cpn>): Compute Akaike Information Criterion (AIC) for a CPN Model

BIC.cpn(): Bayesian Information Criterion for Compound Poisson-Normal Models

anova(<cpn>): Analysis of Deviance for CPN Models

coef(<cpn>): Extract coefficients from a Compound Poisson-Normal model

cpn(): Compound Poisson-Normal Regression

cpn_neg_log_likelihood(): Negative Log-Likelihood for Compound Poisson-Normal Regression

emm_basis.cpn(): Basis for Estimated Marginal Means for Compound Poisson-Normal Models

fitted(<cpn>): Extract Fitted Values from a Compound Poisson-Normal (CPN) Model

logLik(<cpn>): Extract Log-Likelihood from a CPN Model

plot(<cpn>): Plot Diagnostics for a CPN Model

predict(<cpn>): Predict Method for CPN Model Objects

print(<cpn>): Print method for Compound Poisson-Normal model objects

print(<summary.cpn>): Print Method for Summary of CPN Model

recover_data(<cpn>): Recover Data for cpn Model Objects

residuals(<cpn>): Extract Residuals from a Compound Poisson-Normal (CPN) Model

simulate_cpn_data(): Simulate Data from a Compound Poisson-Normal Model

summary(<cpn>): Summarize a Compound Poisson-Normal (CPN) Model Fit

update(<cpn>): Update a CPN Model with a New Formula or Data

vcov(<cpn>): Variance-Covariance Matrix for a CPN Model