For each individual, compute the time spent in each state
compute_time_spent(data)data.frame containing id, id of the trajectory, time, time at which a change occurs
and state, associated state.
a matrix with K columns containing the total time spent in each state for each individual
Other Descriptive statistics:
boxplot.timeSpent(),
compute_duration(),
compute_number_jumps(),
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)
# cut at Tmax = 8
d_JK2 <- cut_data(d_JK, Tmax = 8)
# compute time spent by each id in each state
timeSpent <- compute_time_spent(d_JK2)