dcutter | R Documentation |
If observations must be a data.frame with 4 columns:
observations: A column for the measurements;
LDL: A column for the lower detection limit;
UDL: A column for the upper detection limit;
Cut: A column for the truncated of censored nature of the data.
dcutter(
par,
observations = NULL,
distribution = "gamma",
n.mixture = NULL,
debug = FALSE,
limits.lower = NULL,
limits.upper = NULL,
log = TRUE
)
par |
Values for parameters of distribution |
observations |
The observations; see description. |
distribution |
Can be gamma, normal, weibull, lognormal, or generalized.gamma. |
n.mixture |
Number of distributions |
debug |
If TRUE, show some information. If 2, show more information. |
limits.lower |
Value for lower detection limit |
limits.upper |
Value for upper detection limit |
log |
If TRUE, return the log likelihood |
dcutter returns the density of the cutter function
The density of the cutter function according to observations.
Marc Girondot marc.girondot@gmail.com
Other Distributions:
cutter()
,
dSnbinom()
,
dbeta_new()
,
dggamma()
,
logLik.cutter()
,
plot.cutter()
,
print.cutter()
,
r2norm()
,
rcutter()
,
rmnorm()
,
rnbinom_new()
## Not run:
library(HelpersMG)
par <- c('shape1' = 0.42265849507444225,
'scale1' = 14.139457094879594,
'shape2' = 1.667131542489706,
'scale2' = 0.10763344388223803,
'p1' = 0.12283307526788023)
obs <- data.frame(Observations=c(0.755, 1.013, 2.098, 6.265, 4.708, 0.078, 2.169, 0.403, 1.251,
0.008, 1.419, 1.078, 2.744, 81.534, 1.426, 13.486, 7.813, 0.165,
0.118, 0.864, 0.369, 7.159, 2.605, 1.579, 1.646, 0.484, 4.492,
0.139, 0.28, 0.154, 0.106, 0.104, 4.185, 0.735, 0.149, 0.183,
0.062, 8.246, 0.165, 0.121, 0.109, 0.092, 0.162, 0.108, 0.139,
0.141, 0.124, 0.124, 0.151, 0.141, 0.364, 0.295, 0.09, 0.135,
0.154, 0.218, 0.167, -Inf, 0.203, 0.228, 0.107, 0.162, 0.194,
0.322, 0.351, 0.17, 0.236, 0.176, 0.107, 0.12, 0.095, 0.27, 0.194,
0.125, 0.123, 0.085, 0.164, 0.106, 0.079, 0.162),
LDL=0.001, UDL=NA, Cut="censored")
dcutter(par=par, observations=obs, distribution="gamma",
n.mixture=NULL, debug=FALSE, limits.lower=NULL,
limits.upper=NULL,log=FALSE)
dcutter(par=par, observations=obs, distribution="gamma",
n.mixture=NULL, debug=FALSE, limits.lower=NULL,
limits.upper=NULL, log=TRUE)
## End(Not run)
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