NEWS

---

ptmixed 1.1.3 (2022-08-18)

• Released: August 2022
• Updated vignette with package logo and more detailed installation instructions
• Added xlim argument to make.spaghetti()
• Changed xlab default in pmf()

ptmixed 1.1.2

• Released: April 2022
• Removed dependency on aod package (which is scheduled to be archived by CRAN)

ptmixed 1.1.1

• Released: December 2021
• Fixed problem with NEWS file, which was not visible on CRAN any more

ptmixed 1.1.0

• Released: November 2021
• Updated citation information with details of final (issued) version of the article published in Statistical Modelling in: package description, citation file, help pages and vignettes
• Fixed bug in make.spaghetti() function (rows with NAs on either x or y do not cause problems any more)

ptmixed 1.1

ptmixed 1.0

ptmixed 1.0.3

• Released: February 2021
• Added .checkmle() step in ptmixed() to flag as not converged problematic cases on the boundary of the parameter space

ptmixed 1.0.2

• Released: January 2021
• Updated vignette
• Changed displaying style for function arguments in the documentation
• Corrected BibTeX formatting of author names in CITATION file
• Added to make.spaghetti() code to restore bty, mar and xpd values as they were before the function call

ptmixed 1.0.1

• Released: October 2020
• Updated URL in DESCRIPTION file
• Added na.rm = T in computation of ylim within make.spaghetti()
• Added warnings in simulate_ptglmm

ptmixed 1.0.0

• Released: August 2020
• The article describing the Poisson-Tweedie GLMM is now published in Statistical Modelling! The article is published with Open Access, so anybody can freely download it from the website of Statistical Modelling
• Updated package description, citation info, vignette and help pages to include references to the article
• Added example on how to compute the likelihood ratio test in the vignette
• Added margins and legend.space arguments to make.spaghetti(). Added automatic sorting of provided dataframe ( = no need to pre-sort it any more!)

ptmixed 0.5

ptmixed 0.5.4

• Released: June 2020
• Added link to arXiv preprint in package description and vignette
• Added file with citation info
• Added further arguments to make.spaghetti(); cex.lab argument fixed

ptmixed 0.5.2

• Released: April 2020
• Adapted code so that it runs both for balanced and unbalanced datasets (previously balanced design was assumed)
• Fixed problem with visualization of vignette on CRAN page

ptmixed 0.5.1

• Released: April 2020
• Added vignette to illustrate the functionalities of the package
• Simplified syntax of ptmixed(), ptglm(), nbmixed() and nbglm() (wrt the id and offset arguments). ranef() function updated accordingly
• Added example dataset df1, used in the ptmixed() and nbmixed() help pages. Examples in help pages revised
• Added simulate_ptglmm() function, to be used for illustration purposes (in the vignettes)
• Added pmf() function to visualize the pmf of a discrete variable
• make.spaghetti(): fixed minor bug in that arose when the col argument was specified + added legend.inset argument

ptmixed 0.4

ptmixed 0.4.3

• Released: February 2020
• Added the possibility to use Laplace approximation, which is a special case of the adaptive Gauss Hermite quadrature method where just 1 quadrature point is used (simply set npoints = 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)
• Added make.spaghetti() function to create a spaghetti plot / trajectory plot to visualize longitudinal data
• Added example dataset df1
• Added silent argument to summary.ptglmm(). Furthermore, printed output table with parameter estimates and Wald test is now presented with at most 4 decimals
• Fixed bug that caused ptglm() and nbglm()to print detailed optimization info also when trace = T

ptmixed 0.4.2

• Released: January 2020
• Changed class check within wald.test() to prevent problems with future R release (4.0.0)
• Fixed bug that occurred when freq.updates = 1 was set in ptmixed() and nbmixed()

ptmixed 0.4.1

• Released: October 2019
• Computation of starting values for ptmixed() and nbmixed() improved
• Added wald.test() function for computation of the multivariate Wald test
• Added checks on maxit[1] == 0 within ptglm() and nbglm() so as to make it possible to skip BFGS optimization and go straight to Nelder-Mead
• Help files revised and improved
• Added extra checks in summary.ptglmm() and summary.ptglm() (to verify that the smallest eigenvalue is not too small)

ptmixed 0.3

ptmixed 0.3.1

• Released: September 2019
• Added ptglm() function for the estimation of a Poisson-Tweedie GLM
• Added nbmixed() and nbglm() functions for the estimation of negative binomial GLMM and GLM using the Poisson-Tweedie parametrization (negative binomial: a = 0)
• The package now comprises two classes: 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 implemented
• min.var.init argument added to ptmixed()

ptmixed 0.2

ptmixed 0.2.1

• Released: July 2019
• Added function to compute the empirical Bayes estimates of the random intercept
• Class name of ptmixed() output changed from ptmm to ptglmm
• Corrected typo in summary.ptglmm() function (the MLE of the dispersion parameter was wrongly called “deviance” instead of dispersion in the previous versions)
• Added NEWS file

ptmixed 0.1

ptmixed 0.1.2

• Released: June 2019
• This is a major update aimed at speeding up the maximization of the loglikelihood. When 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 0.0

ptmixed 0.0.4

• Released: May 2019
• ptmixed() now outputs extra information (number of quadrature points used, initial values, warnings)
• A mistake in the computation of the GH quadrature points was introduced from version 0.0.2. This has been fixed in this version

ptmixed 0.0.3

• Released: May 2019
• Fixed a typo in message on initial loglikelihood value that is displayed when trace = T in ptmixed() function
• Added exceptions and warnings for the case that maxit[1] and/or maxit[2] are set = 0

ptmixed 0.0.2

• Released: Apr. 2019
• Function ptmixed() does not require the specification of a time argument any more
• maxit argument default value in function ptmixed() increased to c(1e4, 100)
• Internal function that computes starting values improved
• Added warning with indication that a simpler Poisson mixed model may fit the data sufficiently well
• Added warning when initial estimate of the variance parameter is < 0.001

ptmixed 0.0.1

• Released: Feb. 2019
• First version of the package