Package index • Countr

Countr overview

Countr-package Countr: Flexible Univariate Count Models Based on Renewal Processes

Fit renewal regression models for count data.

Supporting functions for objects fitted with renewalCount().

getParNames(): Return the names of distribution parameters
renewalCoef(): Get named vector of coefficients for renewal objects
renewalCoefList(): Split a vector using the prefixes of the names for grouping
renewalNames(): Get names of parameters of renewal regression models
surv(): Wrapper to built-in survival functions

coef(<renewal>) vcov(<renewal>) residuals(<renewal>) residuals_plot(<renewal>) fitted(<renewal>) confint(<renewal>) summary(<renewal>) print(<renewal>) print(<summary.renewal>) model.matrix(<renewal>) logLik(<renewal>) nobs(<renewal>) extractAIC(<renewal>) addBootSampleObject(<renewal>) df.residual(<renewal>): Methods for renewal objects
se.coef(): Extract Standard Errors of Model Coefficients
predict(<renewal>): Predict method for renewal objects

dCount_conv_bi() dCount_conv_user(): Compute count probabilities using convolution
dCount_conv_loglik_bi() dCount_conv_loglik_user(): Log-likelihood of a count probability computed by convolution (bi)
dmodifiedCount_bi() dmodifiedCount_user(): Compute count probabilities based on modified renewal process (bi)
dWeibullCount() dWeibullCount_loglik() evWeibullCount(): Probability calculations for Weibull count models
dWeibullgammaCount_mat_Covariates(): Univariate Weibull Count Probability with gamma and covariate heterogeneity
evCount_conv_bi() evCount_conv_user(): Expected value and variance of a renewal count process
dBivariateWeibullCountFrankCopula() dBivariateWeibullCountFrankCopula_loglik(): Density and log-likelihood of the Bivariate Frank Copula Weibull Count model
dRenewalFrankCopula_user() dRenewalFrankCopula_bi(): Bivariate Count probability Using Frank copula (user)