View source: R/Tagloss_simulate.R
Tagloss_simulate | R Documentation |
Generate data with known features.
model_before is applied to par parameter.
model_after is applied after par is separated in p1, p2, pL1, pL2, pR1 and pR2 parameters.
pobservation can be a vector of daily probabilities to be captured. The last value is repeated
if necessary.
The maximum number of days of observation is exp(LengthObservation["max"]).
If model="12" then par must have _1 and _2 parameters.
if model="LR" then par must have _L2, _L1, _R2, R1 parameters.
Tagloss_simulate(
n = 500,
par,
pobservation = c(rep(0.05, 70), 0.01),
LengthObservation = c(min = 0, max = 9),
dailysurvival = 0.999,
model = "12",
model_before = NULL,
model_after = NULL,
progressbar = TRUE
)
n |
Number of individuals to simulate |
par |
Set of parameters |
pobservation |
Probability of daily observation |
LengthObservation |
The log of number of days of observations is a random number between min and max |
dailysurvival |
Daily probability of survival |
model |
Must be "12" or "LR" |
model_before |
Transformation of parameters before to use Tagloss_model() |
model_after |
Transformation of parameters after to use Tagloss_model() |
progressbar |
Is a progressbar should be shown? |
Tagloss_simulate returns a list with the number of days different kinds of individuals are seen.
Return a list with the number of days different kinds of individuals are seen.
Marc Girondot marc.girondot@gmail.com
Other Model of Tag-loss:
Tagloss_L()
,
Tagloss_LengthObs()
,
Tagloss_cumul()
,
Tagloss_daymax()
,
Tagloss_fit()
,
Tagloss_format()
,
Tagloss_mcmc()
,
Tagloss_mcmc_p()
,
Tagloss_model()
,
logLik.Tagloss()
,
o_4p_p1p2
,
plot.Tagloss()
,
plot.TaglossData()
library(phenology)
## Not run:
# Example
par <- structure(c(49.5658922243074, 808.136085362158, 106.283783786853,
5.22150592456511, 8.00608716525864, 8.32718202233396, 150.612916258503,
715.865805125223, 2242.06574225966, 119.212383120678, 10.1860735529433,
7.14231725937626), .Names = c("D1_2", "D2D1_2", "D3D2_2", "A_2",
"B_2", "C_2", "D1_1", "D2D1_1", "D3D2_1", "A_1", "B_1", "C_1"))
cmr <- Tagloss_simulate(n=500,
par=par, model="12")
cmr_f <- Tagloss_format(cmr, model="12")
## End(Not run)
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