## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----install, eval = FALSE----------------------------------------------------
# # from a local source:
# install.packages("smartcor", repos = NULL, type = "source")
# 
# # or use devtools from the package directory:
# devtools::install("path/to/smartcor")

## ----library------------------------------------------------------------------
library(smartcor)

## ----pairwise-----------------------------------------------------------------
# continuous + continuous → Pearson
smart_cor(mtcars$mpg, mtcars$wt)

## ----pairwise-binary----------------------------------------------------------
# continuous + binary → point-biserial (= Pearson)
smart_cor(mtcars$mpg, mtcars$vs)

## ----ordinal------------------------------------------------------------------
# numeric variables with ≤10 unique values are treated as ordinal by default;
# assume_latent_normal controls whether polychoric or Kendall is used
smart_cor(mtcars$gear, mtcars$carb, assume_latent_normal = FALSE)

## ----categorical--------------------------------------------------------------
# some categorical data
colour = factor(sample(c("red", "blue", "green"), 100, replace = TRUE))
shape  = factor(sample(c("circle", "square", "triangle"), 100, replace = TRUE))
smart_cor(colour, shape)

## ----override-----------------------------------------------------------------
# force cyl to be treated as continuous
smart_cor(mtcars$mpg, mtcars$cyl, y_type = "continuous")

## ----force-method-------------------------------------------------------------
smart_cor(mtcars$mpg, mtcars$wt, method = "spearman")

## ----cormat-------------------------------------------------------------------
mat = smart_cormat(
  mtcars[, c("mpg", "cyl", "vs", "gear")],
  assume_latent_normal = FALSE
)
mat

## ----tidy---------------------------------------------------------------------
res = smart_cor(mtcars$mpg, mtcars$wt, verbose = FALSE)
tidy(res)

## ----tidy-mat-----------------------------------------------------------------
tidy(mat)

## ----available----------------------------------------------------------------
available_methods("ordinal", "ordinal")
available_methods("continuous", "binary")
available_methods("categorical", "categorical")

## ----auto, eval = FALSE-------------------------------------------------------
# # runs the LR test and picks polychoric or Kendall accordingly:
# smart_cor(mtcars$gear, mtcars$carb)