robustbase: Interfaces for robustbase package for data science pipelines.

In rbertolusso/intubate: Interface to Popular R Functions for Data Science Pipelines

Description

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

Usage

ntbt_adjbox(data, ...)
ntbt_glmrob(data, ...)
ntbt_lmrob(data, ...)
ntbt_ltsReg(data, ...)
ntbt_nlrob(data, ...)

Arguments

data	data frame, tibble, list, ...
...	Other arguments passed to the corresponding interfaced function.

Details

Interfaces call their corresponding interfaced function.

Value

Object returned by interfaced function.

Author(s)

Roberto Bertolusso

Examples

## Not run: 
library(intubate)
library(magrittr)
library(robustbase)


## ntbt_adjbox: Plot an Adjusted Boxplot for Skew Distributions
## Original function to interface
adjbox(len ~ dose, data = ToothGrowth)

## The interface puts data as first parameter
ntbt_adjbox(ToothGrowth, len ~ dose)

## so it can be used easily in a pipeline.
ToothGrowth %>%
  ntbt_adjbox(len ~ dose)


## ntbt_glmrob: Robust Fitting of Generalized Linear Models
data(carrots)

## Original function to interface
glmrob(cbind(success, total-success) ~ logdose + block,
       family = binomial, data = carrots, method= "Mqle",
       control= glmrobMqle.control(tcc=1.2))

## The interface puts data as first parameter
ntbt_glmrob(carrots, cbind(success, total-success) ~ logdose + block,
            family = binomial, method= "Mqle",
            control= glmrobMqle.control(tcc=1.2))

## so it can be used easily in a pipeline.
carrots %>%
  ntbt_glmrob(cbind(success, total-success) ~ logdose + block,
              family = binomial, method= "Mqle",
              control= glmrobMqle.control(tcc=1.2))


## ntbt_lmrob: MM-type Estimators for Linear Regression
data(coleman)

## Original function to interface
set.seed(0)
lmrob(Y ~ ., data = coleman, setting = "KS2011")

## The interface puts data as first parameter
ntbt_lmrob(coleman, Y ~ ., setting = "KS2011")

## so it can be used easily in a pipeline.
coleman %>%
  ntbt_lmrob(Y ~ ., setting = "KS2011")


## ntbt_ltsReg: Least Trimmed Squares Robust (High Breakdown) Regression
data(stackloss)

## Original function to interface
ltsReg(stack.loss ~ ., data = stackloss)

## The interface puts data as first parameter
ntbt_ltsReg(stackloss, stack.loss ~ .)

## so it can be used easily in a pipeline.
stackloss %>%
  ntbt_ltsReg(stack.loss ~ .)


## ntbt_nlrob: Robust Fitting of Nonlinear Regression Models
DNase1 <- DNase[ DNase$Run == 1, ]

## Original function to interface
nlrob(density ~ Asym/(1 + exp(( xmid - log(conc) )/scal ) ),
      data = DNase1, trace = TRUE,
      start = list( Asym = 3, xmid = 0, scal = 1 ))

## The interface puts data as first parameter
ntbt_nlrob(DNase1, density ~ Asym/(1 + exp(( xmid - log(conc) )/scal ) ),
           trace = TRUE,
           start = list( Asym = 3, xmid = 0, scal = 1 ))

## so it can be used easily in a pipeline.
DNase1 %>%
  ntbt_nlrob(density ~ Asym/(1 + exp(( xmid - log(conc) )/scal ) ),
             trace = TRUE,
             start = list( Asym = 3, xmid = 0, scal = 1 ))

## End(Not run)

rbertolusso/intubate documentation built on May 27, 2019, 3 a.m.