Chris Brien

Assists in automating the selection of terms to include in mixed models when 'asreml' is used to fit the models. Also used to display, in tables and graphs, predictions obtained using any model fitting function and to explore differences between predictions. The content falls into the following natural groupings: (i) Data, (ii) Object manipulation functions, (iii) Model modification functions, (iv) Model testing functions, (v) Model diagnostics functions, (vi) Prediction production and presentation functions, (vii) Response transformation functions, and (viii) Miscellaneous functions (for further details see 'asremlPlus-package' in help). A history of the fitting of a sequence of models is kept in a data frame. Procedures are available for choosing models that conform to the hierarchy or marginality principle and for displaying predictions for significant terms in tables and graphs. The 'asreml' package provides a computationally efficient algorithm for fitting mixed models using Residual Maximum Likelihood. It is a commercial package that can be purchased from 'VSNi' <http://www.vsni.co.uk/> as 'asreml-R', who will supply a zip file for local installation/updating (see <http://asreml.org/>). It is not needed for functions that are methods for 'alldiffs' and 'data.frame' objects. The package 'asremPlus' can also be installed from <http://chris.brien.name/rpackages/>.

The content falls into the following groupings: (i) Data, (ii) Factor manipulation functions, (iii) Design functions, (iv) ANOVA functions, (v) Matrix functions, (vi) Projector and canonical efficiency functions, and (vii) Miscellaneous functions. There is a vignette describing how to use the design functions for randomizing and assessing designs available as a vignette called 'DesignNotes'. The ANOVA functions facilitate the extraction of information when the 'Error' function has been used in the call to 'aov'. The package 'dae' can also be installed from <http://chris.brien.name/rpackages/>.

Assists in producing longitudinal or profile plots of measured traits. These allow checks to be made for anomalous data and growth patterns in the data to be explored. Smoothing of growth trends for individual plants using smoothing splines is available for removing transient effects. There are tools for diagnosing the adequacy of trait smoothing, either using this package or other packages, such as those that fit nonlinear growth models. A range of per-unit (pot, plant, plot) growth traits can be extracted from longitudinal data, including single time-point smoothed trait values and their growth rates, interval growth rates and other growth statistics, such as maximum growth. The package is particularly suited to preparing data from high-throughput phenotyping facilities, such as imaging data from a Lemna-Tec Scananalyzer (see <https://www.lemnatec.com/products/conveyor-scanalyzer/> for more information). The package 'growthPheno' can also be installed from <http://chris.brien.name/rpackages/>.

Note that 'imageData' has been superseded by 'growthPheno'. The package 'growthPheno' incorporates all the functionality of 'imageData' and has functionality not available in 'imageData', but some 'imageData' functions have been renamed. The 'imageData' package is no longer maintained, but is retained for legacy purposes.