Determine probability of reporting under a Poisson arrival Process
Determine probability of reporting under a Poisson arrival Process
Determines the probability that claims occuring under a Poisson process with arrival intensity expo and reporting delay distribution dist during the time between t_min and t_max are reported between tau_min and tau_max.
dist: A reporting delay Distribution, or a compiled interval probability function.
intervals: A data frame with columns xmin, xmax, tmin, tmax. Claims occur within [xmin, xmax] and be reported within [tmin, tmax].
expo: Poisson intensity. If given, must be a vectorised function that yields the intensity of the claim arrival process at a specified time. expo = NULL is equivalent to a constant intensity function. expo is only relevant up to a multiplicative constant.
with_params: Parameters of dist to use. Can be a parameter set with different values for each interval. If dist is a compiled interval probability function, with_params can be a matrix instead.
.tolerance: Absolute element-wise tolerance.
.max_iter: Maximum number of iterations. The number of integration intervals will be at most length(lower) * .max_iter. Therefor the maximum number of function evaluations per integration interval will be 15 * .max_iter.
.try_compile: Try compiling the distributions probability function to speed up integration?
Returns
A vector of reporting probabilities, with one entry per row of intervals.
Details
The reporting probability is given by
P(x + d in [tmin, tmax] | x in [xmin, xmax]) = E(P(x + d in [tmin, tmax] | x) | x in [xmin, xmax]) / P(x in [xmin, xmax]) = int_[xmin, xmax] expo(x) P(x + d in [tmin, tmax]) dx = int_[xmin, xmax] expo(x) P(d in [tmin - x, tmax - x]) dx / int_[xmin, xmax] expo(x) dx
prob_report uses integrate_gk() to compute the two integrals.