intubate (version 1.0.0)

glmx: Interfaces for glmx package for data science pipelines.

Description

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

Usage

ntbt_glmx(data, ...)
ntbt_hetglm(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(glmx)
# 
# ## ntbt_glmx: Generalized Linear Models with Extra Parameters
# set.seed(1)
# d <- data.frame(x = runif(200, -1, 1))
# d$y <- rnbinom(200, mu = exp(0 + 3 * d$x), size = 1)
# require("MASS")
# 
# ## Original function to interface
# glmx(y ~ x, data = d, family = negative.binomial, xlink = "log", xstart = 0)
# 
# ## The interface puts data as first parameter
# ntbt_glmx(d, y ~ x, family = negative.binomial, xlink = "log", xstart = 0)
# 
# ## so it can be used easily in a pipeline.
# d %>%
#   ntbt_glmx(y ~ x, family = negative.binomial, xlink = "log", xstart = 0)
# 
# 
# ## ntbt_hetglm: Heteroskedastic Binary Response GLMs
# n <- 200
# x <- rnorm(n)
# ystar <- 1 + x +  rnorm(n, sd = exp(x))
# y  <- factor(ystar > 0) 
# dta <- data.frame(x, y)
# 
# ## Original function to interface
# hetglm(y ~ x | 1, data = dta)
# 
# ## The interface puts data as first parameter
# ntbt_hetglm(dta, y ~ x | 1)
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_hetglm(y ~ x | 1)
# ## End(Not run)