plot_ordinal_cohens_kappa function

Constructs a serial dependence plot based on the ordinal Cohen's kappa considering the block distance

plot_ordinal_cohens_kappa constructs a serial dependence plot of an ordinal time series based on the ordinal Cohen's kappa considering the block distance UTF-8

plot_ordinal_cohens_kappa(
  series,
  states,
  max_lag = 10,
  alpha = 0.05,
  plot = TRUE,
  title = "Serial dependence plot",
  bar_width = 0.12,
  ...
)

Arguments

• series: An OTS.
• states: A numerical vector containing the corresponding states.
• max_lag: The maximum lag represented in the plot (default is 10).
• alpha: The significance level for the corresponding hypothesis test (default is 0.05).
• plot: Logical. If plot = TRUE (default), returns the serial dependence plot. Otherwise, returns a list with the values of the ordinal Cohens's kappa, the critical value and the corresponding p-values.
• title: The title of the graph.
• bar_width: The width of the corresponding bars.
• ...: Additional parameters for the function.

Returns

If plot = TRUE (default), returns the serial dependence plot based on the ordinal Cohens's kappa. Otherwise, the function returns a list with the values of the ordinal Cohens's kappa, the critical value and the corresponding p-values.

Details

Constructs a serial dependence plot based on the ordinal Cohens's kappa, $\widehat{\kappa}_d(l)$, for several lags, where $d$ is the block distance between ordinal states, that is, $d(s_i, s_j)=|i-j|$ for two states $s_i$ and $s_j$. A dashed lined is incorporated indicating the critical value of the test based on the following asymptotic approximation (under the i.i.d. assumption):

where $T$ is the series length, $\widehat{f_k}$ is the estimated cumulative probability for state $s_k$

and $\widehat{disp}_d$ is the DIVC estimate of the dispersion.

Examples

plot_ock <- plot_ordinal_cohens_kappa(series = AustrianWages$data[[100]],
states = 0 : 5, max_lag = 3) # Representing
# the serial dependence plot
list_ck <- plot_ordinal_cohens_kappa(series = AustrianWages$data[[100]],
states = 0 : 5, max_lag = 3, plot = FALSE) # Obtaining
# the values of the ordinal Cohens's kappa, the critical value and the p-values

References

Rdpack::insert_ref(key="weiss2019distance",package="otsfeatures")

Author(s)

Ángel López-Oriona, José A. Vilar