intubate (version 1.0.0)

lmtest: Interfaces for lmtest package for data science pipelines.

Description

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

Usage

ntbt_bgtest(data, ...)
ntbt_bptest(data, ...)
ntbt_coxtest(data, ...)
ntbt_dwtest(data, ...)
ntbt_encomptest(data, ...)
ntbt_gqtest(data, ...)
ntbt_grangertest(data, ...)
ntbt_harvtest(data, ...)
ntbt_hmctest(data, ...)
ntbt_jtest(data, ...)
ntbt_raintest(data, ...)
ntbt_resettest(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(lmtest)
# 
# ## ntbt_bgtest: Breusch-Godfrey Test for higher-order serial correlation
# x <- rep(c(1, -1), 50)
# y1 <- 1 + x + rnorm(100)
# dta <- data.frame(x, y1)
# 
# ## or for fourth-order serial correlation
# ## Original function to interface
# bgtest(y1 ~ x, order = 4, data = dta)
# 
# ## The interface puts data as first parameter
# ntbt_bgtest(dta, y1 ~ x, order = 4)
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_bgtest(y1 ~ x, order = 4)
# 
# 
# ## ntbt_bptest: Breusch-Pagan test against heteroskedasticity
# ## ntbt_gqtest: Goldfeld-Quandt test against heteroskedasticity
# ## ntbt_hmctest: Harrison-McCabe test for heteroskedasticity
# x <- rep(c(-1,1), 50)
# err1 <- c(rnorm(50, sd=1), rnorm(50, sd=2))
# err2 <- rnorm(100)
# y1 <- 1 + x + err1
# y2 <- 1 + x + err2
# dtah <- data.frame(x, y1, y2)
# 
# ## Original function to interface
# bptest(y1 ~ x, data = dtah)
# gqtest(y1 ~ x, data = dtah)
# hmctest(y1 ~ x, data = dtah)
# bptest(y2 ~ x, data = dtah)
# gqtest(y2 ~ x, data = dtah)
# hmctest(y2 ~ x, data = dtah)
# 
# ## The interface puts data as first parameter
# ntbt_bptest(dtah, y1 ~ x)
# ntbt_gqtest(dtah, y1 ~ x)
# ntbt_hmctest(dtah, y1 ~ x)
# ntbt_bptest(dtah, y2 ~ x)
# ntbt_gqtest(dtah, y2 ~ x)
# ntbt_hmctest(dtah, y2 ~ x)
# 
# ## so it can be used easily in a pipeline.
# dtah %>%
#   ntbt_bptest(y1 ~ x)
# dtah %>%
#   ntbt_gqtest(y1 ~ x)
# dtah %>%
#   ntbt_hmctest(y1 ~ x)
# dtah %>%
#   ntbt_bptest(y2 ~ x)
# dtah %>%
#   ntbt_gqtest(y2 ~ x)
# dtah %>%
#   ntbt_hmctest(y2 ~ x)
# 
# 
# ## ntbt_coxtest: Cox Test for Comparing Non-Nested Models
# ## ntbt_encomptest: encompassing test of Davidson & MacKinnon for comparing non-nested models
# ## ntbt_jtest: Davidson-MacKinnon J test for comparing non-nested models
# data(USDistLag)
# usdl <- na.contiguous(cbind(USDistLag, lag(USDistLag, k = -1)))
# colnames(usdl) <- c("con", "gnp", "con1", "gnp1")
# 
# ## Original function to interface
# coxtest(con ~ gnp + con1, con ~ gnp + gnp1, data = usdl)
# encomptest(con ~ gnp + con1, con ~ gnp + gnp1, data = usdl)
# jtest(con ~ gnp + con1, con ~ gnp + gnp1, data = usdl)
# 
# ## The interface puts data as first parameter
# ntbt_coxtest(usdl, con ~ gnp + con1, con ~ gnp + gnp1)
# ntbt_encomptest(usdl, con ~ gnp + con1, con ~ gnp + gnp1)
# ntbt_jtest(usdl, con ~ gnp + con1, con ~ gnp + gnp1)
# 
# ## so it can be used easily in a pipeline.
# usdl %>%
#   ntbt_coxtest(con ~ gnp + con1, con ~ gnp + gnp1)
# usdl %>%
#   ntbt_encomptest(con ~ gnp + con1, con ~ gnp + gnp1)
# usdl %>%
#   ntbt_jtest(con ~ gnp + con1, con ~ gnp + gnp1)
# 
# ## ntbt_dwtest: Durbin-Watson test for autocorrelation of disturbances
# err1 <- rnorm(100)
# x <- rep(c(-1,1), 50)
# y1 <- 1 + x + err1
# err2 <- filter(err1, 0.9, method="recursive")
# y2 <- 1 + x + err2
# dta <- data.frame(y1, y2, x)
# 
# ## Original function to interface
# dwtest(y1 ~ x, data = dta)
# dwtest(y2 ~ x, data = dta)
# 
# ## The interface puts data as first parameter
# ntbt_dwtest(dta, y1 ~ x)
# ntbt_dwtest(dta, y2 ~ x)
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_dwtest(y1 ~ x)
# dta %>%
#   ntbt_dwtest(y2 ~ x)
# 
# 
# ## ntbt_grangertest: Test for Granger Causality
# data(ChickEgg)
# ## Original function to interface
# grangertest(egg ~ chicken, order = 3, data = ChickEgg)
# grangertest(chicken ~ egg, order = 3, data = ChickEgg)
# 
# ## The interface puts data as first parameter
# ntbt_grangertest(ChickEgg, egg ~ chicken, order = 3)
# ntbt_grangertest(ChickEgg, chicken ~ egg, order = 3)
# 
# ## so it can be used easily in a pipeline.
# ChickEgg %>%
#   ntbt_grangertest(egg ~ chicken, order = 3)
# ChickEgg %>%
#   ntbt_grangertest(chicken ~ egg, order = 3)
# 
# 
# ## ntbt_harvtest: Harvey-Collier test for linearity
# x <- 1:50
# y1 <- 1 + x + rnorm(50)
# y2 <- y1 + 0.3*x^2
# dta <- data.frame(y1, x)
# 
# ## Original function to interface
# harvtest(y1 ~ x, data = dta)
# 
# ## The interface puts data as first parameter
# ntbt_harvtest(dta, y1 ~ x)
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_harvtest(y1 ~ x)
# 
# ## ntbt_raintest: Rainbow test for linearity
# x <- c(1:30)
# y <- x^2 + rnorm(30,0,2)
# dta <- data.frame(x, y)
# 
# ## Original function to interface
# raintest(y ~ x, data = dta)
# 
# ## The interface puts data as first parameter
# ntbt_raintest(dta, y ~ x)
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_raintest(y ~ x)
# 
# 
# ## ntbt_resettest: Ramsey's RESET test for functional form
# x <- c(1:30)
# y1 <- 1 + x + x^2 + rnorm(30)
# y2 <- 1 + x + rnorm(30)
# dta <- data.frame(x, y1, y2)
# 
# ## Original function to interface
# resettest(y1 ~ x , power=2, type="regressor", data = dta)
# resettest(y2 ~ x , power=2, type="regressor", data = dta)
# 
# ## The interface puts data as first parameter
# ntbt_resettest(dta, y1 ~ x , power=2, type="regressor")
# ntbt_resettest(dta, y2 ~ x , power=2, type="regressor")
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_resettest(y1 ~ x , power=2, type="regressor")
# dta %>%
#   ntbt_resettest(y2 ~ x , power=2, type="regressor")
# ## End(Not run)