![[R logo]](../../../doc/html/logo.jpg)
| AustralianElections | elections to Australian House of Representatives, 1949-2004 |
| betaHPD | compute and optionally plot beta HDRs |
| bioChemists | article production by graduate students in biochemistry Ph.D. programs |
| coef.hurdle | summarize hurdle regression models for count data |
| coef.zeroinfl | summary of zero-inflated regression models for count data |
| computeMargins | add information about voting outcomes to a rollcall object |
| constrain.items | constrain item parameters in analysis of roll call data |
| constrain.legis | constrain legislators' ideal points in analysis of roll call data |
| convertCodes | convert entries in a rollcall matrix to binary form |
| densigamma | inverse-Gamma distribution |
| dropRollCall | drop user-specified elements from a rollcall object |
| dropUnanimous | drop unanimous votes from rollcall objects and matrices |
| extractRollCallObject | return the roll call object used in fitting an ideal model |
| hurdle | hurdle models for count data |
| ideal | analysis of roll call data (IRT models) via Markov chain Monte Carlo methods |
| idealToMCMC | convert an object of class ideal to a coda MCMC object |
| igamma | inverse-Gamma distribution |
| igammaHDR | inverse-Gamma distribution |
| logLik.hurdle | hurdle models for count data |
| logLik.zeroinfl | zero-inflated regression models for count data |
| ntable | nicely formatted tables |
| odTest | likelihood ratio test for over-dispersion in count data |
| partycodes | political parties appearing in the U.S. Congress |
| pigamma | inverse-Gamma distribution |
| plot.ideal | plots an ideal object |
| plot.predict.ideal | plot methods for predictions from ideal objects |
| plot1d | plots an ideal object |
| plot2d | plots an ideal object |
| postProcess | remap MCMC output via affine transformations |
| predict.ideal | predicted probabilities from an ideal object |
| predict.zeroinfl | generate predictions from zero-inflated regression count models |
| predprob | compute predicted probabilities from fitted models |
| predprob.glm | Predicted Probabilties for GLM Fits |
| predprob.ideal | predicted probabilities from fitting ideal to rollcall data |
| predprob.zeroinfl | predicted probabilities from zero-inflated regression models |
| print.hurdle | hurdle models for count data |
| print.predict.ideal | predicted probabilities from an ideal object |
| print.summary.hurdle | summarize hurdle regression models for count data |
| print.summary.rollcall | summarize a rollcall object |
| print.summary.zeroinfl | summary of zero-inflated regression models for count data |
| print.zeroinfl | zero-inflated regression models for count data |
| prussian | Prussian army horse kick data |
| qigamma | inverse-Gamma distribution |
| readKH | read roll call data in Poole-Rosenthal KH format |
| rigamma | inverse-Gamma distribution |
| rollcall | create an object of class rollcall |
| s109 | rollcall object, 109th U.S. Senate |
| sc9497 | votes from the United States Supreme Court, from 1994-1997 |
| state.info | information about the American states needed for U.S. Congress |
| summary.hurdle | summarize hurdle regression models for count data |
| summary.ideal | summary of an ideal object |
| summary.rollcall | summarize a rollcall object |
| summary.zeroinfl | summary of zero-inflated regression models for count data |
| tracex | trace plot of MCMC iterates, posterior density of legislators' ideal points |
| unionDensity | cross national rates of trade union density |
| vectorRepresentation | convert roll call matrix to series of vectors |
| vuong | Vuong's non-nested hypothesis test |
| zeroinfl | zero-inflated regression models for count data |