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

## ----univariate-data----------------------------------------------------------
# Load the example data included with dyadicMarkov
utils::data("dyadic_univariate_example", package = "dyadicMarkov")

head(dyadic_univariate_example)
dim(dyadic_univariate_example)

## ----univariate-states--------------------------------------------------------
table(dyadic_univariate_example$FM)
table(dyadic_univariate_example$SM)

## ----univariate-counts--------------------------------------------------------
emp_uni <- dyadicMarkov::countEmp(
  chainFM = dyadic_univariate_example$FM,
  chainSM = dyadic_univariate_example$SM,
  states = 2L
)

print(emp_uni)
summary(emp_uni)

## ----univariate-mle-----------------------------------------------------------
fit_uni <- dyadicMarkov::mleEstimation(emp_uni)

print(fit_uni)
summary(fit_uni)

## ----pattern-methods, fig.width=8.5, fig.height=4.1, out.width="99%", fig.align="center"----
pat_uni <- dyadicMarkov::univariatePattern(
  chainFM = dyadic_univariate_example$FM,
  chainSM = dyadic_univariate_example$SM,
  states = 2L,
  alpha = 0.05
)

print(pat_uni)
summary(pat_uni)
plot(pat_uni)

## ----reverse-perspective------------------------------------------------------
pat_uni_reverse <- dyadicMarkov::univariatePattern(
  chainFM = dyadic_univariate_example$SM,
  chainSM = dyadic_univariate_example$FM,
  states = 2L,
  alpha = 0.05
)

pat_uni_reverse