ctsfeatures (version 1.2.2)

plot_cohen: Constructs a serial dependence plot based on Cohen's kappa

Description

plot_cohen constructs a serial dependence plot of a categorical time series based on Cohen's kappa

Usage

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

Value

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

Arguments

series

An object of type tsibble (see R package tsibble), whose column named Value contains the values of the corresponding CTS. This column must be of class factor and its levels must be determined by the range of the CTS.

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 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.

Author

Ángel López-Oriona, José A. Vilar

Details

Constructs a serial dependence plot based on Cohens's kappa, \(\widehat{\kappa}(l)\), for several lags. A dashed lined is incorporated indicating the critical value of the test based on the following asymptotic approximation (under the i.i.d. assumption): $$\sqrt{\frac{T}{V(\widehat{\boldsymbol p})}}\bigg(\widehat{\kappa}(l)+\frac{1}{T}\bigg)\sim N\big(0, 1\big),$$ where \(T\) is the series length, \(\widehat{\boldsymbol p}=(\widehat{p}_1, \ldots, \widehat{p}_r)\) is the vector of estimated marginal probabilities for the \(r\) categories of the series and \(V(\boldsymbol {\widehat{p}})=1-\frac{1+2\sum_{i=1}^{r}\widehat{p}_i^3-3\sum_{i=1}^{r}\widehat{p}_i^2}{(1-\sum_{i=1}^{r}\widehat{p}_i^2)^2}\).

References

weiss2011empiricalctsfeatures

Examples

sequence_1 <- GeneticSequences[which(GeneticSequences$Series==1),]
plot_ck <- plot_cohen(series = sequence_1, max_lag = 3) # Representing
# the serial dependence plot
list_ck <- plot_cohen(series = sequence_1, max_lag = 3, plot = FALSE) # Obtaining
# the values of Cohens's kappa, the critical value and the p-values