The aim of this document is to keep track of the changes made to the
different versions of the R
package ptmixed
.
The numbering of package versions follows the convention a.b.c, where a and b are non-negative integers and c is a positive integer. When minor changes are made to the package, a and b are kept fixed and only c is increased. Major changes to the package, instead, are made apparent by changing a or b.
Each section of this document corresponds to a major change in the package - in other words, within a section you will find all those package versions a.b.x where a and b are fixed whereas x = 1, 2, 3, … Each subsection corresponds to a specific package version.
xlim
argument to make.spaghetti()
xlab
default in pmf()
aod
package (which is scheduled to be
archived by CRAN
)NEWS
file, which was not visible on CRAN
any
moremake.spaghetti()
function (rows with NA
s on either
x
or y
do not cause problems any more).checkmle()
step in ptmixed()
to flag as not converged
problematic cases on the boundary of the parameter spacemake.spaghetti()
code to restore bty
, mar
and xpd
values as they were before the function callna.rm = T
in computation of ylim
within make.spaghetti()
simulate_ptglmm
margins
and legend.space
arguments to make.spaghetti()
.
Added automatic sorting of provided dataframe ( = no need to
pre-sort it any more!)make.spaghetti()
; cex.lab
argument
fixedptmixed()
, ptglm()
, nbmixed()
and
nbglm()
(wrt the id
and offset
arguments). ranef()
function
updated accordinglydf1
, used in the ptmixed()
and nbmixed()
help pages. Examples in help pages revisedsimulate_ptglmm()
function, to be used for illustration
purposes (in the vignettes)pmf()
function to visualize the pmf of a discrete variablemake.spaghetti()
: fixed minor bug in that arose when the col
argument was specified + added legend.inset
argumentnpoints = 1
in
ptmixed()
or nbmixed()
). Note: use of the Laplace is not
recommended, because it is less accurate than the adaptive GH,
results in lower convergence rates and can yield biased parameter
estimates! We recommend using a sufficient number of quadrature
points (5 typically produces a good likelihood approximation)make.spaghetti()
function to create a spaghetti plot /
trajectory plot to visualize longitudinal datadf1
silent
argument to summary.ptglmm()
. Furthermore, printed
output table with parameter estimates and Wald test is now presented
with at most 4 decimalsptglm()
and nbglm()
to print detailed
optimization info also when trace = T
wald.test()
to prevent problems with
future R
release (4.0.0)freq.updates = 1
was set in
ptmixed()
and nbmixed()
ptmixed()
and nbmixed()
improvedwald.test()
function for computation of the multivariate
Wald testmaxit[1] == 0
within ptglm()
and nbglm()
so as
to make it possible to skip BFGS optimization and go straight to
Nelder-Meadsummary.ptglmm()
and summary.ptglm()
(to
verify that the smallest eigenvalue is not too small)ptglm()
function for the estimation of a Poisson-Tweedie GLMnbmixed()
and nbglm()
functions for the estimation of
negative binomial GLMM and GLM using the Poisson-Tweedie
parametrization (negative binomial: a = 0)ptglmm
for objects obtained
from ptmixed()
and nbmixed()
, and ptglm
for objects obtained
from ptglm()
and nbglm()
. Summary functions for objects of both
classes have been implementedmin.var.init
argument added to ptmixed()
ptmixed()
output changed from ptmm
to ptglmm
summary.ptglmm()
function (the MLE of the
dispersion parameter was wrongly called “deviance” instead of
dispersion in the previous versions)ptmixed()
is called, it first attempts to
maximize the loglikelihood with the Nelder-Mead algorithm and then,
if this fails, with the BFGS algorithm. Until version 0.0.4 the
quadrature points were updated at every iteration for both
Nelder-Mead and BFGS. Starting from this version, when Nelder-Mead
is called it is possible to update the positioning of the quadrature
points every n iterations by setting the freq.updates
argument
equal to n. Default is set to freq.updates = 200
(this typically
makes the optimization about 10 times faster than when
freq.updates = 1
)ptmixed()
now outputs extra information (number of quadrature
points used, initial values, warnings)trace = T
in ptmixed()
functionmaxit[1]
and/or
maxit[2]
are set = 0ptmixed()
does not require the specification of a time
argument any moremaxit
argument default value in function ptmixed()
increased to
c(1e4, 100)Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.