The CDatanet package implements the count data model with social interactions and the dyadic linking model developed in Houndetoungan (2020).
It also simulates data from the count data model and implements the Spatial Autoregressive Tobit model (LeSage, 2000; Xu and Lee, 2015) for left censored data and the Spatial Autoregressive Model (Lee, 2004).
To make the computations faster CDatanet uses C++ through the Rcpp package (Eddelbuettel et al., 2011).
Atchade, Y. F., & Rosenthal, J. S. (2005). On adaptive markov chain monte carlo algorithms, Bernoulli, 11(5), 815-828, 10.3150/bj/1130077595
Eddelbuettel, D., Fran<U+00E7>ois, R., Allaire, J., Ushey, K., Kou, Q., Russel, N., ... & Bates, D., 2011,
Rcpp: Seamless R and C++ integration, Journal of Statistical Software, 40(8), 1-18, 10.18637/jss.v040.i08
Houndetoungan, E. A., 2020, A Count Data Model with Social Interactions. Available at SSRN 3721250, 10.2139/ssrn.3721250
Lee, L. F., 2004, Asymptotic distributions of quasi-maximum likelihood estimators for spatial autoregressive models. Econometrica, 72(6), 1899-1925, 10.1111/j.1468-0262.2004.00558.x
LeSage, J. P., 2000, Bayesian estimation of limited dependent variable spatial autoregressive models, Geographical Analysis, 32(1), 19-35, 10.1111/j.1538-4632.2000.tb00413.x
Xu, X., & Lee, L. F., 2015, Maximum likelihood estimation of a spatial autoregressive Tobit model, Journal of Econometrics, 188(1), 264-280, 10.1016/j.jeconom.2015.05.004
simCDnet, CDnetNPL, SARML, SARTML and netformation.