r_MTS {ARPobservation} | R Documentation |
Random generation of behavior streams (based on an alternating renewal process) of a specified length and with specified mean event durations, mean interim times, event distribution, and interim distribution, which are then coded as momentary time sampling data with given interval length between moments.
r_MTS(
n,
mu,
lambda,
stream_length,
F_event,
F_interim,
interval_length,
summarize = FALSE,
equilibrium = TRUE,
p0 = 0,
tuning = 2
)
n |
number of behavior streams to generate |
mu |
mean event duration |
lambda |
mean interim time |
stream_length |
length of behavior stream |
F_event |
distribution of event durations. Must be of class |
F_interim |
distribution of interim times. Must be of class |
interval_length |
length of time between moments |
summarize |
logical value indicating whether the vector of moments should be summarized by taking their mean, excluding the first moment in each row. |
equilibrium |
logical; if |
p0 |
Initial state probability. Only used if |
tuning |
controls the size of the chunk of random event durations and interim times. Adjusting this may be useful in order to speed computation time. |
Generates behavior streams by repeatedly drawing random event durations and random interim times from the distributions as specified, until the sum of the durations and interim times exceeds the requested stream length. Then applies a momentary time sampling filter to the generated behavior streams.
If summarize = FALSE
, a matrix of logicals with rows equal to n
and length equal to (stream_length/interval_length) + 1
. If summarize = TRUE
, a vector of means of length n
.
Daniel Swan <dswan@utexas.edu>
# A set of unsummarized MTS observations
r_MTS(n = 5, mu = 2, lambda = 4, stream_length = 20,
F_event = F_exp(), F_interim = F_exp(), interval_length = 1)
# A set of summarized MTS observations
r_MTS(n = 5, mu = 2, lambda = 4, stream_length = 20,
F_event = F_exp(), F_interim = F_exp(),
interval_length = 1, summarize = TRUE)