Changes in version 1.0.1

The new version follows the major revision of the paper in April 2022

Some function name has changed

SART model under rational expectations

It is now possible to estimate the SART model under rational expectations. In the previous version, the SART model is only available under complete information.

Changes in version 2.0.1

This version follows the major revision of the paper in September 2022. - The count data model includes a more flexible specification. Especially, it is possible to assume that the cut points are not equally spaced for large values of the dependent variable. - I also implement a network formation model with degree heterogeneity as fixed effects (see Yan et al., 2019). - Models under incomplete information are now estimated using LBFGS algorithm of the package RcppNumerical. Thus, the optimization is performed in C++ and is very fast compared to the version 1.0.1.

Changes in versions 2.0.2 and 2.0.3

Note and Warning found in the check for MACOS have been fixed

Changes in version 2.1.0

R defaulted to C++11 in R 4.0.0, to C++14 in R 4.2.0 and to C++17.

Changes in version 2.1.1

Fixed effect is allowed in the model SAR.

Changes in version 2.1.2

Address the case where a subnetwork consists of a single agent. AIC and BIC are added to the output of cdnet. They can be used to choose Rbar.

Changes in version 2.1.3

homophily has been changed to homophily.re for the random effect models. homophily.FE has heen changed to homophily.fe Random effects in homophily.re can be one side or two sides. Fixed effects in homophily.fe can be one side or two sides. Symmetric network models are included in homophily.re. Symmetric network models are included in homophily.fe The function homophili.data is added to convert data between directed network models and symmetric network models.