Creates simple to highly customized tables for a wide selection of descriptive statistics, with or without weighting the data.

Fits the space-time Epidemic Type Aftershock Sequence
    ('ETAS') model to earthquake catalogs using a stochastic 'declustering' 
    approach. The 'ETAS' model is a 'spatio-temporal' marked point process
    model and a special case of the 'Hawkes' process. The package is based 
    on a Fortran program by 'Jiancang Zhuang'
    (available at <http://bemlar.ism.ac.jp/zhuang/software.html>),
    which is modified and translated into C++ and C such that it 
    can be called from R. Parallel computing with 'OpenMP' is possible 
    on supported platforms.

The 2-D spatial and temporal Epidemic Type Aftershock Sequence ('ETAS') Model is widely used to 'decluster' earthquake data catalogs. Usually, the calculation of standard errors of the 'ETAS' model parameter estimates is based on the Hessian matrix derived from the log-likelihood function of the fitted model. However, when an 'ETAS' model is fitted to a local data set over a time period that is limited or short, the standard errors based on the Hessian matrix may be inaccurate. It follows that the asymptotic confidence intervals for parameters may not always be reliable. As an alternative, this package allows the building of bootstrap confidence intervals based on empirical quantiles for the parameters of the 2-D spatial and temporal 'ETAS' model.

Estimation of the components of an ETAS (Epidemic Type Aftershock Sequence) model for earthquake description. Non-parametric background seismicity can be estimated through FLP (Forward Likelihood Predictive). New version 2.0.0: covariates have been introduced to explain the effects of external factors on the induced seismicity; the parametrization has been changed; Chiodi, Adelfio (2017)<doi:10.18637/jss.v076.i03>.

Treatments of a one-way layout, being equivalent to a control, 
 can be selected with this package. Bonferroni adjusted "two one-sided 
 t-tests" (TOST) and related simultaneous confidence intervals are given for 
 both differences or ratios of means of normally distributed data. For the 
 case of equal variances and balanced sample sizes for the treatment groups, 
 the single-step procedure of Bofinger and Bofinger (1995) 
 <doi:10.1111/j.2517-6161.1995.tb02058.x> can be chosen. For non-normal data, 
 the Wilcoxon test is applied.