intubate (version 1.0.0)

mgcv: Interfaces for mgcv package for data science pipelines.

Description

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

Usage

ntbt_bam(data, ...)
ntbt_gamm(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(mgcv)
# 
# ## ntbt_bam: Generalized additive models for very large datasets
# set.seed(3)
# dat <- gamSim(1,n=25000,dist="normal",scale=20)
# bs <- "cr"
# k <- 12
# 
# ## Original function to interface
# bam(y ~ s(x0, bs=bs) + s(x1, bs=bs) + s(x2, bs=bs, k=k) + s(x3, bs=bs), data = dat)
# 
# ## The interface puts data as first parameter
# ntbt_bam(dat, y ~ s(x0, bs=bs) + s(x1, bs=bs) + s(x2, bs=bs, k=k) + s(x3, bs=bs))
# 
# ## so it can be used easily in a pipeline.
# dat %>%
#   ntbt_bam(y ~ s(x0, bs=bs) + s(x1, bs=bs) + s(x2, bs=bs, k=k) + s(x3, bs=bs))
# 
# 
# ## ntbt_gam: Generalized additive models with integrated smoothness estimation
# set.seed(2) ## simulate some data... 
# dat <- gamSim(1, n = 400, dist = "normal", scale = 2)
# ## Original function to interface
# gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat)
# 
# ## The interface puts data as first parameter
# ntbt_gam(dat, y ~ s(x0) + s(x1) + s(x2) + s(x3))
# 
# ## so it can be used easily in a pipeline.
# dat %>%
#   ntbt_gam(y ~ s(x0) + s(x1) + s(x2) + s(x3))
# 
# 
# ## ntbt_gamm: Generalized Additive Mixed Models
# set.seed(0)
# dat <- gamSim(1, n = 200, scale = 2)
# 
# ## Original function to interface
# gamm(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat)
# 
# ## The interface puts data as first parameter
# ntbt_gamm(dat, y ~ s(x0) + s(x1) + s(x2) + s(x3))
# 
# ## so it can be used easily in a pipeline.
# dat %>%
#   ntbt_gamm(y ~ s(x0) + s(x1) + s(x2) + s(x3))
# ## End(Not run)