Computes qf of the composite model.
qcomposite(p, spec1, arg1, spec2, arg2, initial = 1, lower.tail = TRUE, log.p = FALSE)
scalar or vector of probabilities to compute the qf.
a character string specifying the head parent distribution (for example, "lnorm" if the parent distribution corresponds to the lognormal).
list of arguments/parameters of the head parent distribution.
a character string specifying the tail parent distribution (for example, "exp" if the parent distribution corresponds to the exponential).
list of arguments/parameters of the tail parent distribution.
initial values of the threshold, \(\theta\).
logical; if TRUE
, probabilities are p
, otherwise 1-p
.
logical; if TRUE
, probabilities p
are returned as log(p
).
An object of the same length as p
, giving the qf values computed at p
.
The qf of composite model has a general form of:
$$Q(p) = Q_{1}(p(1+\phi)F_{1}(\theta)) \mbox{ if } \quad p \leq \frac{1}{1+\phi}, $$ $$= Q_{2} \left( F_{2}(\theta) + (1-F_{2}(\theta)) \left( \frac{p(1+\phi)-1}{\phi} \right)\right) \mbox{ if } \quad p > \frac{1}{1+\phi} $$ whereby \(\phi\) is the weight component, \(\theta\) is the threshold and \(F_{i}(x)\) for \(i=1,2\) are the qfs correspond to head and tail parent distributions, respectively.
Abu Bakar, S. A., Nadarajah, S., Adzhar, Z. A. A. K., & Mohamed, I. (2016). gendist: An R package for generated probability distribution models. PloS one, 11(6). Cooray, K., & Ananda, M. M. (2005). Modeling actuarial data with a composite lognormal-Pareto model. Scandinavian Actuarial Journal, 2005(5), 321-334. Scollnik, D. P. (2007). On composite lognormal-Pareto models. Scandinavian Actuarial Journal, 2007(1), 20-33. Nadarajah, S., & Bakar, S. A. A. (2014). New composite models for the Danish fire insurance data. Scandinavian Actuarial Journal, 2014(2), 180-187. Bakar, S. A., Hamzah, N. A., Maghsoudi, M., & Nadarajah, S. (2015). Modeling loss data using composite models. Insurance: Mathematics and Economics, 61, 146-154.
# NOT RUN {
x=runif(10, min=0, max=1)
y=qcomposite(x, spec1="lnorm", arg1=list(meanlog=0.1,sdlog=0.2), spec2="exp",
arg2=list(rate=0.5) )
# }
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