Import, process, summarize and visualize raw data from 
    metabolic carts. See Robergs, Dwyer, and Astorino (2010) <doi:10.2165/11319670-000000000-00000> for more details on data processing.

The Splancs package was written as an enhancement to S-Plus for display and analysis of spatial point pattern data; it has been ported to R and is in "maintenance mode".

This program calculates bioclimatic indices and fluxes (radiation, 
    evapotranspiration, soil moisture) for use in studies of ecosystem function, 
    species distribution, and vegetation dynamics under changing climate 
    scenarios. Predictions are based on a minimum of required inputs: latitude, 
    precipitation, air temperature, and cloudiness. 
    Davis et al. (2017) <doi:10.5194/gmd-10-689-2017>.

The current version of this package estimates spatial autoregressive models for binary dependent variables using GMM estimators <doi:10.18637/jss.v107.i08>. It supports one-step (Pinkse and Slade, 1998) <doi:10.1016/S0304-4076(97)00097-3> and two-step GMM estimator along with the linearized GMM estimator proposed by Klier and McMillen (2008) <doi:10.1198/073500107000000188>. It also allows for either Probit or Logit model and compute the average marginal effects. All these models are presented in Sarrias and Piras (2023) <doi:10.1016/j.jocm.2023.100432>.

An extension to the individual claim simulator called 'SynthETIC'
    (on CRAN), to simulate the evolution of case estimates of incurred losses
    through the lifetime of an insurance claim. The transactional simulation
    output now comprises key dates, and both claim payments and revisions of
    estimated incurred losses. An initial set of test parameters, designed to
    mirror the experience of a real insurance portfolio, were set up and applied
    by default to generate a realistic test data set of incurred histories (see
    vignette). However, the distributional assumptions used to generate this
    data set can be easily modified by users to match their experiences.
    Reference: Avanzi B, Taylor G, Wang M (2021) "SPLICE: A Synthetic Paid Loss
    and Incurred Cost Experience Simulator" <arXiv:2109.04058>.