Package index • underdisp

Package overview

underdisp underdisp-package: underdisp: Diagnostics and Models for Underdispersed Count Data

Screening and diagnostics

ud_screen(): Screen a count outcome for underdispersion
compare_dispersion(): Compare count-model dispersion across the model family
dispersion_test(): Regression-adjusted test of equidispersion
dispersion_profile() plot(<dispersion_profile>): Dispersion profile: variance-to-mean ratio against the fitted mean
zi_test(): Boundary-corrected test for zero-inflation (CPB vs ZI-CPB)
rootogram(): Hanging rootogram for a fitted count model
pit_hist(): Non-randomized PIT histogram for a fitted count model

Estimators

One formula interface, one class per model, one set of methods.

cpb(): Fit a Continuous Parameter Binomial (CPB) regression
gec(): Generalized event count (Katz-family) regression
count_reg(): Matched count regressions: Poisson, negative binomial, COM-Poisson, generalized Poisson, gamma-count, double Poisson

High-dimensional fixed effects

cpb_fe(): CPB regression with high-dimensional unit fixed effects
gec_fe(): GEC (Katz-family) regression with high-dimensional unit fixed effects

Hurdle models

hurdle_cpb(): Hurdle continuous parameter binomial regression
hurdle_gec(): Hurdle GEC (Katz-family) regression
hurdle_count(): Hurdle count regression for the matched count families

Zero-inflated models

zi_cpb(): Zero-inflated continuous parameter binomial regression
zi_gec(): Zero-inflated GEC (Katz-family) regression
zi_count(): Zero-inflated count regression for the matched count families

Inference and summaries

summary(<cpb>): Summarize a CPB fit
confint(<cpb>): Confidence intervals for a CPB fit
confint(<gec>) confint(<cpb_fe>) confint(<count_reg>) confint(<zi_count>) confint(<hurdle_cpb>) confint(<hurdle_gec>) confint(<hurdle_count>) confint(<zi_cpb>) confint(<zi_gec>): Confidence intervals for every model class
alpha_confint(): Profile-likelihood interval for the dispersion parameter alpha
calibrate_alpha(): Calibrate the interval for the CPB dispersion parameter
vcov(<cpb_fe>): Bootstrap covariance for a fixed-effects CPB fit
fitted(<cpb_fe>) fitted(<hurdle_cpb>) fitted(<hurdle_gec>) fitted(<hurdle_count>) fitted(<zi_cpb>) fitted(<zi_gec>) fitted(<zi_count>): Fitted means for the two-part and fixed-effects classes

Predictions

predict(<cpb>): Predictions from a CPB fit
predict(<cpb_fe>): Predictions from a fixed-effects CPB fit
predict(<gec>): Predictions from a generalized event count fit
predict(<count_reg>): Predictions from a matched count-family fit
predict(<hurdle_cpb>): Predict from a hurdle-CPB fit
predict(<hurdle_gec>): Predict from a hurdle-GEC fit
predict(<hurdle_count>): Predict from a hurdle Poisson/NB fit
predict(<zi_cpb>): Predict from a zi_cpb fit
predict(<zi_gec>): Predict from a zi_gec fit
predict(<zi_count>): Predict from a zero-inflated Poisson/NB fit

Quantities of interest

first_difference(): First difference for a CPB fit
first_difference(<gec>) first_difference(<gec_fe>) first_difference(<cpb_fe>) first_difference(<hurdle_gec>) first_difference(<zi_gec>) first_difference(<count_reg>) first_difference(<hurdle_count>) first_difference(<zi_count>): First differences for the matched count families
first_difference(<hurdle_cpb>) first_difference(<zi_cpb>): Extensive/intensive first-difference decomposition for a hurdle- or ZI-CPB
implied_ceiling(): Implied ceiling with a profile-likelihood interval
irr(): Incidence rate ratios for a CPB fit
irr(<count_reg>) irr(<gec>) irr(<gec_fe>) irr(<cpb_fe>) irr(<hurdle_gec>) irr(<zi_gec>) irr(<hurdle_count>) irr(<zi_count>): Rate and odds ratios for the matched count families

Model comparison and scoring

compare_models(): Compare fitted underdispersed-count models
score(): Proper scoring rules for a fitted count model
cv_score(): Cross-validated proper scores for a count model

Panel tools

mundlak(): Mundlak (correlated random effects) device

Simulation and distribution functions

simulate(<cpb>) simulate(<cpb_fe>) simulate(<gec>) simulate(<count_reg>) simulate(<hurdle_cpb>) simulate(<hurdle_gec>) simulate(<hurdle_count>) simulate(<zi_cpb>) simulate(<zi_gec>) simulate(<zi_count>): Simulate responses from a fitted underdisp model
dcpb() pcpb() qcpb(): Continuous parameter binomial distribution functions
rcpb(): Simulate from the continuous parameter binomial
rhurdle_cpb(): Simulate from the hurdle continuous parameter binomial
rzicpb(): Simulate from the zero-inflated continuous parameter binomial
dgec() pgec() qgec() rgec(): Generalized event count (Katz) distribution functions
dcompois() pcompois() qcompois() rcompois(): Conway–Maxwell–Poisson distribution functions
dgammacount() pgammacount() qgammacount() rgammacount(): Gamma-count distribution functions
ddoublepois() pdoublepois() qdoublepois() rdoublepois(): Double Poisson distribution functions
dgenpois() pgenpois() qgenpois() rgenpois(): Generalized Poisson distribution functions

broom methods

tidy(<cpb>) tidy(<cpb_fe>) tidy(<hurdle_cpb>) tidy(<zi_cpb>) tidy(<gec>) tidy(<hurdle_gec>) tidy(<zi_gec>) tidy(<count_reg>) tidy(<zi_count>) tidy(<hurdle_count>): Tidy a CPB fit (broom method)
glance(<cpb>) glance(<cpb_fe>) glance(<hurdle_cpb>) glance(<zi_cpb>) glance(<gec>) glance(<hurdle_gec>) glance(<zi_gec>) glance(<count_reg>) glance(<zi_count>) glance(<hurdle_count>): Glance at a CPB fit (broom method)
augment(<cpb>): Augment data with CPB fitted values (broom method)

Data

peacekeeping: UN peacekeeping contributions, state-years