For each individual, compute the number of jumps performed
compute_number_jumps(data, countDuplicated = FALSE)data.frame containing id, id of the trajectory, time, time at which a change occurs and
state, associated state.
if TRUE, jumps in the same state are counted as jump
A vector containing the number of jumps for each individual
Other Descriptive statistics:
boxplot.timeSpent(),
compute_duration(),
compute_time_spent(),
estimate_pt(),
hist.duration(),
hist.njump(),
plot.pt(),
plotData(),
statetable(),
summary_cfd()
# Simulate the Jukes-Cantor model of nucleotide replacement
K <- 4
PJK <- matrix(1 / 3, nrow = K, ncol = K) - diag(rep(1 / 3, K))
lambda_PJK <- c(1, 1, 1, 1)
d_JK <- generate_Markov(n = 10, K = K, P = PJK, lambda = lambda_PJK, Tmax = 10)
# compute the number of jumps
nJump <- compute_number_jumps(d_JK)