parallel, spatstat, EBImage, tiff, stats, grDevices

Volker Schmid [aut, cre], Priyanka Kukreja [ctb], Fabian Scheipl [ctb]
c(
person("Volker", "Schmid", role = c("aut", "cre"), email = "stats@volkerschmid.de"),
person("Priyanka", "Kukreja", role = "ctb"),
person("Fabian", "Scheipl", role = "ctb")
)
parallel, tiff, stats, grDevices, utils, EBImage
Tools for 3D imaging, mostly for biology/microscopy.
Read and write TIFF stacks. Functions for segmentation, filtering and analysing 3D point patterns.

parallel, tiff, stats, grDevices, utils, EBImage, httr

Volker Schmid [aut, cre],
Priyanka Kukreja [ctb],
Fabian Scheipl [ctb]

Tools for 3D imaging, mostly for biology/microscopy.
Read and write TIFF stacks. Functions for segmentation, filtering and analyzing 3D point patterns.

Simulation of Dynamic Microbial Inactivation
c(person("Alberto", "Garre Perez", email = "garre.alberto@gmail.com", role = c("aut", "cre")),
person("Pablo S.", "Fernandez Egea", email = "pablo.fernandez@upct.es", role = "aut"),
person("Jose A.", "Egea Larrosa", email = "josea.egea@upct.es", role = "aut")
)
Prediction and adjustment to experimental data of microbial
inactivation. Several models available in the literature are implemented.
Alberto Garre Perez [aut, cre],
Pablo S. Fernandez Egea [aut],
Jose A. Egea Larrosa [aut]

c(person("Alberto", "Garre", email = "garre.alberto@gmail.com", role = c("aut", "cre")),
person("Pablo S.", "Fernandez", email = "pablo.fernandez@upct.es", role = "aut"),
person("Jose A.", "Egea", email = "josea.egea@upct.es", role = "aut")
)
Alberto Garre [aut, cre],
Pablo S. Fernandez [aut],
Jose A. Egea [aut]

Mathematical Modelling of (Dynamic) Microbial Inactivation
Functions for modelling microbial inactivation under
isothermal or dynamic conditions. The calculations are based on several mathematical models broadly
used by the scientific community and industry. Functions enable to make predictions for cases where the
kinetic parameters are known. It also implements functions for parameter estimation for isothermal and
dynamic conditions. The model fitting capabilities include an Adaptive Monte Carlo method for a Bayesian
approach to parameter estimation.