A collection of functions to do model-based phylogenetic analysis. 
    It includes functions to calculate community phylogenetic diversity,
    to estimate correlations among functional traits while accounting for 
    phylogenetic relationships, and to fit phylogenetic generalized linear
    mixed models. The Bayesian phylogenetic generalized linear mixed models
    are fitted with the 'INLA' package (<https://www.r-inla.org>).

Provides general linear model facilities (single y-variable, multiple x-variables with arbitrary mixture of continuous and categorical and arbitrary interactions) for cross-species data. The method is, however, based on the nowadays rather uncommon situation in which uncertainty about a phylogeny is well represented by adopting a single polytomous tree. The theory is in A. Grafen (1989, Proc. R. Soc. B 326, 119-157) and aims to cope with both recognised phylogeny (closely related species tend to be similar) and unrecognised phylogeny (a polytomy usually indicates ignorance about the true  sequence of binary splits).

Contains a function to categorize accelerometer readings collected in free-living (e.g., for 24 hours/day for 7 days), preprocessed and compressed as counts (unit-less value) in a specified time period termed epoch (e.g., 1 minute) as either bedrest (sleep) or active.  The input is a matrix with a timestamp column and a column with number of counts per epoch. The output is the same dataframe with an additional column termed bedrest. In the bedrest column each line (epoch) contains a function-generated classification 'br' or 'a' denoting bedrest/sleep and activity, respectively.  The package is designed to be used after wear/nonwear marking function in the 'PhysicalActivity' package.  Version 1.1 adds preschool thresholds and corrects for possible errors in algorithm implementation.

It provides a function "wearingMarking" for classification of monitor
    wear and nonwear time intervals in accelerometer data collected to assess
    physical activity. The package also contains functions for making plot for 
    accelerometer data and obtaining the summary of various information including 
    daily monitor wear time and the mean monitor wear time during valid days.      
    "deliveryPred" and "markDelivery" can classify days for ActiGraph delivery by mail;
    "deliveryPreprocess" can process accelerometry data for analysis by zeropadding incomplete 
    days and removing low activity days; "markPAI" can categorize physical activity
    intensity level based on user-defined cut-points of accelerometer counts. It also
    supports importing ActiGraph AGD files with "readActigraph" and "queryActigraph" functions.