Provides MCMC algorithms for the analysis of
        zero-inflated count models. The case of stochastic search
        variable selection (SVS) is also considered.  All MCMC samplers
        are coded in C++ for improved efficiency. A data set
        considering the demand for health care is provided.

Zillow, an online real estate company, provides real estate
    and mortgage data for the United States through a REST API. The
    ZillowR package provides an R function for each API service, making it
    easy to make API calls and process the response into convenient,
    R-friendly data structures.  See
    <https://www.zillow.com/howto/api/APIOverview.htm> for the Zillow API
    Documentation. NOTE: Zillow deprecated their API on 2021-09-30, and
    this package is now deprecated as a result.

Analyze count time series with excess zeros. 
    Two types of statistical models are supported: Markov regression by Yang et al.
    (2013) <doi:10.1016/j.stamet.2013.02.001> and state-space models by Yang et al. 
    (2015) <doi:10.1177/1471082X14535530>. They are also known as observation-driven and 
    parameter-driven models respectively in the time series literature. The functions used for 
    Markov regression or observation-driven models can also be used to fit ordinary regression models 
    with independent data under the zero-inflated Poisson (ZIP) or zero-inflated negative binomial (ZINB) 
    assumption. Besides, the package contains some miscellaneous functions to compute density, distribution, 
    quantile, and generate random numbers from ZIP and ZINB distributions.

Generates Realizations of First-Order Integer Valued Autoregressive Processes with Zero-Inflated Innovations (ZINAR(1)) and Estimates its Parameters as described in Garay et al. (2021) <doi:10.1007/978-3-030-82110-4_2>.

Simulation, exploratory data analysis and Bayesian analysis of the p-order Integer-valued Autoregressive (INAR(p)) and Zero-inflated p-order Integer-valued Autoregressive (ZINAR(p)) processes, as described in Garay et al. (2020) <doi:10.1080/00949655.2020.1754819>.