intubate (version 1.0.0)

arm: Interfaces for arm package for data science pipelines.

Description

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

Usage

ntbt_bayesglm(data, ...)
ntbt_bayespolr(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(arm)
# 
# ## ntbt_bayesglm: Bayesian generalized linear models
# n <- 100
# x1 <- rnorm (n)
# x2 <- rbinom (n, 1, .5)
# b0 <- 1
# b1 <- 1.5
# b2 <- 2
# y <- rbinom(n, 1, invlogit(b0+b1*x1+b2*x2))
# 
# dta <- data.frame(y, x1, x2)
# 
# ## Original function to interface
# bayesglm(y ~ x1 + x2, family = binomial(link="logit"), data = dta,
#          prior.scale = Inf, prior.df = Inf)
# 
# ## The interface puts data as first parameter
# ntbt_bayesglm(dta, y ~ x1 + x2, family = binomial(link="logit"),
#               prior.scale = Inf, prior.df = Inf)
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_bayesglm(y ~ x1 + x2, family = binomial(link="logit"),
#                 prior.scale = Inf, prior.df = Inf)
# 
# 
# ## ntbt_bayespolr: Bayesian Ordered Logistic or Probit Regression
# ## Original function to interface
# bayespolr(Sat ~ Infl + Type + Cont, weights = Freq, data = housing,
#           prior.scale = Inf, prior.df = Inf)
# 
# ## The interface puts data as first parameter
# ntbt_bayespolr(housing, Sat ~ Infl + Type + Cont, weights = Freq,
#                prior.scale = Inf, prior.df = Inf)
# 
# ## so it can be used easily in a pipeline.
# housing %>%
#   ntbt_bayespolr(Sat ~ Infl + Type + Cont, weights = Freq,
#                  prior.scale = Inf, prior.df = Inf)
# ## End(Not run)