# Changes in version 1.0.1

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

- The count data model has changed. It is now possible to have several
gamma parameters instead of gamma = 1 as assumed in the previous
version.
- In the count data model identification, sigma is now set to 1,
because there are several gamma’s.
- The network formation model now includes two unobserved effects
instead of one.

## Some function name has
changed

`SARML`

has been replaced by `sar`

.
`SARTML`

has been replaced by `sart`

.
`CDnetNPL`

has been replaced by `cdnet`

.
`simSARnet`

has been replaced by
`simsar`

.
`simTobitnet`

has been replaced by
`simsart`

.
`simCDnet`

has been replaced by
`simcdnet`

.
`netformation`

has been replaced by
`homophily`

.

## 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.