intubate (version 1.0.0)

caper: Interfaces for caper package for data science pipelines.

Description

Interfaces to caper functions that can be used in a pipeline implemented by magrittr.

Usage

ntbt_brunch(data, ...)
ntbt_crunch(data, ...)
ntbt_macrocaic(data, ...)
ntbt_pgls(data, ...)

Arguments

data

data frame, tibble, list, ...

...

Other arguments passed to the corresponding interfaced function.

Value

Object returned by interfaced function.

Details

Interfaces call their corresponding interfaced function.

Examples

## Not run: 
# library(intubate)
# library(magrittr)
# library(caper)
# 
# ## ntbt_brunch: Calculate a linear model using the brunch algorithm
# data(perissodactyla)
# perisso <- comparative.data(perissodactyla.tree, perissodactyla.data, Binomial)
# 
# ## Original function to interface
# brunch(log.female.wt ~ Territoriality, data = perisso)
# 
# ## The interface puts data as first parameter
# ntbt_brunch(perisso, log.female.wt ~ Territoriality)
# 
# ## so it can be used easily in a pipeline.
# perisso %>%
#   ntbt_brunch(log.female.wt ~ Territoriality)
# 
# 
# ## ntbt_crunch: Calculate a linear model using the crunch algorithm
# data(shorebird)
# shorebird <- comparative.data(shorebird.tree, shorebird.data, Species)
# 
# ## Original function to interface
# crunch(Egg.Mass ~ F.Mass + M.Mass, data = shorebird)
# 
# ## The interface puts data as first parameter
# ntbt_crunch(shorebird, Egg.Mass ~ F.Mass + M.Mass)
# 
# ## so it can be used easily in a pipeline.
# shorebird %>%
#   ntbt_crunch(Egg.Mass ~ F.Mass + M.Mass)
# 
# 
# ## ntbt_macrocaic: Comparative analysis using independent
# ##                 contrasts on species richness data
# data(IsaacEtAl)
# primates <- comparative.data(primates.tree, primates.data, binomial, na.omit=FALSE)
# 
# ## Original function to interface
# macrocaic(species.rich ~ body.mass, data = primates)
# 
# ## The interface puts data as first parameter
# ntbt_macrocaic(primates, species.rich ~ body.mass)
# 
# ## so it can be used easily in a pipeline.
# primates %>%
#   ntbt_macrocaic(species.rich ~ body.mass)
# 
# 
# 
# ## ntbt_pgls: Phylogenetic generalized linear models
# data(shorebird)
# shorebird <- comparative.data(shorebird.tree, shorebird.data, Species, vcv=TRUE, vcv.dim=3)
# 
# ## Original function to interface
# pgls(log(Egg.Mass) ~ log(M.Mass) * log(F.Mass), shorebird, lambda='ML')
# 
# ## The interface puts data as first parameter
# ntbt_pgls(shorebird, log(Egg.Mass) ~ log(M.Mass) * log(F.Mass), lambda='ML')
# 
# ## so it can be used easily in a pipeline.
# shorebird %>%
#   ntbt_pgls(log(Egg.Mass) ~ log(M.Mass) * log(F.Mass), lambda='ML')
# ## End(Not run)