transition_chisq {AnimalSequences} | R Documentation |
Perform a Chi-Squared Test for Transition Counts
Description
This function performs a chi-squared test to determine if there are significant differences between observed and expected transition counts in sequences. It calculates the chi-squared statistic and tests the null hypothesis that transitions occur according to the expected frequencies.
Usage
transition_chisq(sequences, alpha = 0.05)
Arguments
sequences |
A vector of sequences, where each sequence is a character string with elements separated by spaces. |
alpha |
A numeric value representing the significance level for the chi-squared test. Default is 0.05. |
Details
The function calculates observed transition counts from the input sequences, computes expected transition counts based on row and column sums, and performs a chi-squared test to compare observed and expected counts. The test determines if the transitions in the sequences differ significantly from what would be expected by chance.
Value
A list with two elements:
significant |
A logical value indicating whether the chi-squared test result is significant at the given significance level. |
p_value |
A numeric value representing the p-value of the chi-squared test. |
Examples
# Define sequences
sequences <- c('e1 e2 e3', 'e2 e1 e3', 'e3 e2 e1')
# Perform chi-squared test
transition_chisq(sequences, alpha = 0.05)