Observations with NAs of irrelevant variables are no longer
removed
Extended unit tests
Added R >= 3.5.0 dependency
PAGFL 1.1.3 (stable version)
Added a progress bar displaying the percentage of convergence to
pagfl and tv_pagfl if verbose is
selected
Slight changes in the formatting of the print method
for summary of pagfl and
grouped_plm objects
Fix of missing regressor name in the output of pagfl
and grouped_plm when having a single regressor and passing
an empty formula
Deprecation of DGP argument in
sim_tv_DGP
Bugfix when passing a prescribed coefficient matrix and selecting
dynamic = TRUE in sim_DGP
Bugfix to preclude explosive processes when selecting
dynamic = TRUE in sim_tv_DGP
Added seeds to all function examples
Support for RcppArmadillo 14.4.0
PAGFL 1.1.2
Fixed backwards compatibility issue with the generic functions
fitted and resid
Bugfix when passing index variables and an empty formula
y ~ . for tv_pagfl and
grouped_tv_plm
Improved documentation
Changed x-axis label in the plot produced by calling
summary() of a tvpagfl object
Bugfix in the plot produced by calling fitted() and
passing a character time-index variable
Added the current algorithm iteration and tuning parameter as a
progress counter to the console for pagfl and
tv_pagfl if option verbose is selected
Changed the IC selecting the best fitting tuning parameter for the
tv_pagfl and grouped_tv_plm procedures to
include the logarithmic mean squared error as the fitness term
PAGFL 1.1.1
Introduction of grouped_plm and
grouped_tv_plm to estimate grouped (time-varying) panel
data models given an exogenous group structure
Remove warm-starts when iterating across different tuning
parameters
Small efficiency upgrades
More extensive unit testing
Improved documentation
Small updates to generic methods
PAGFL 1.1.0
Introduction of the time-varying PAGFLtv_pagfl
Introduction of s3 methods (summary(),
coef(), fitted(), resid()) for
the output of pagfl and tv_pagfl
Change of the user interface to formula objects
Implementation of unit testing
Renamed functions to be consistently snake case
Support for unordered and/ or unbalanced panel data sets via
index
Possibility to estimate a mix of time-constant and time-varying
coefficients in the same panel data model (const_coef)
Added row and column names to the estimation output
Maximum within-group heterogeneity group_tol set to a
machine inaccuracy value
Improved documentation, checks, and error/warning messages
Enabled 64bit C++ compiler to support large datasets
Improvements to efficiency and numerical stability