cfda (version 0.12.1)

estimate_pt: Estimate probabilities to be in each state

Description

Estimate probabilities to be in each state

Usage

estimate_pt(data, NAafterTmax = FALSE, timeValues = NULL)

Value

A list of two elements:

• t: vector of time

• pt: a matrix with K (= number of states) rows and with length(t) columns containing the probabilities to be in each state at each time.

Arguments

data

data.frame containing id, id of the trajectory, time, time at which a change occurs and state, associated state.

NAafterTmax

if TRUE, return NA if t > Tmax otherwise return the state associated with Tmax (useful when individuals has different lengths)

timeValues

time values at which probabilities are computed, if NULL, unique(data$time) are used

Author

Cristian Preda, Quentin Grimonprez

See Also

plot.pt

Other Descriptive statistics: boxplot.timeSpent(), compute_duration(), compute_number_jumps(), compute_time_spent(), hist.duration(), hist.njump(), plot.pt(), plotData(), statetable(), summary_cfd()

Examples

# 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)

d_JK2 <- cut_data(d_JK, 10)

# estimate probabilities
estimate_pt(d_JK2)