clmplus.AggregateDataPP: Fit Chain Ladder Plus to reverse time triangles.

In clmplus: Tool-Box of Chain Ladder Plus Models

Fit Chain Ladder Plus to reverse time triangles.

Description

Method to fit Chain Ladder plus models to AggregateDataPP objects.

Usage

## S3 method for class 'AggregateDataPP'
clmplus(
  AggregateDataPP,
  hazard.model = NULL,
  link = c("log", "logit"),
  staticAgeFun = TRUE,
  periodAgeFun = "NP",
  cohortAgeFun = NULL,
  effect_log_scale = TRUE,
  constFun = function(ax, bx, kt, b0x, gc, wxt, ages) list(ax = ax, bx = bx, kt = kt, b0x
    = b0x, gc = gc),
  ...
)

Arguments

AggregateDataPP	AggregateDataPP object, reverse time triangle to be fitted.
hazard.model	character, hazard model supported from our package. The model can be chosen from: 'a': Age model, this is equivalent to the Mack chain-ladder. 'ac': Age and cohort effects. 'ap': Age and cohort effects. 'apc': Age cohort and period effects.
link	character, defines the link function and random component associated with the mortality model. "log" would assume that deaths follow a Poisson distribution and use a log link while "logit" would assume that deaths follow a Binomial distribution and a logit link. To be disregarded unless the practitioner specifies his own hazard model in StMoMo.
staticAgeFun	logical, indicates if a static age function \alpha_x is to be included. To be disregarded unless the practitioner specifies his own hazard model in StMoMo.
periodAgeFun	list, a list of length N with the definitions of the period age modulating parameters \beta_x^{(i)}. Each entry can take values: "NP" for non-parametric age terms, "1" for \beta_x^{(i)}=1 or a predefined parametric function of age (see details). Set this to NULL if there are no period terms in the model. To be disregarded unless the practitioner specifies his own hazard model in StMoMo.
cohortAgeFun	character or function, defines the cohort age modulating parameter \beta_x^{(0)}. It can take values: "NP" for non-parametric age terms, "1" for \beta_x^{(0)}=1, a predefined parametric function of age (see details) or NULL if there is no cohort effect. To be disregarded unless the practitioner specifies his own hazard model in StMoMo.
effect_log_scale	logical, whether effects should be on the logarithmic scale. By default, TRUE.
constFun	function, it defines the identifiability constraints of the model. It must be a function of the form constFun <- function(ax, bx, kt, b0x, gc, wxt, ages) taking a set of fitted model parameters and returning a list list(ax = ax, bx = bx, kt = kt, b0x = b0x, gc = gc) of the model parameters with the identifiability constraints applied. If omitted no identifiability constraints are applied to the model. To be disregarded unless the practitioner specifies his own hazard model in StMoMo.
...	parameters to be passed to clmplus.

Value

An object of class clmplusmodel. A list with the following elements:

model.fit	fitStMoMo object, specified hazard model fit from StMoMo.
apc_input	list object. A list containing the following model inputs in age-period-cohort notation: J (integer) Run-off triangle dimension. eta (numeric) Expected time-to-event in the cell. I.e., lost exposure. diagonal (numeric) Cumulative payments last diagonal. hazard.model (character), hazard model specified from the user. Set to user.specific when a custom model is passed.
hazard_scaled_deviance_residuals	matrix array Triangle of the scaled deviance residuals.
fitted_development_factors	matrix array Triangle of the fitted development factors.
fitted_effects	list List of the development-accident-calendar effects fitted.

References

Pittarello, Gabriele, Munir Hiabu, and Andrés M. Villegas. "Replicating and extending chain ladder via an age-period-cohort structure on the claim development in a run-off triangle." arXiv preprint arXiv:2301.03858 (2023).

Examples

data(sifa.mtpl)
sifa.mtpl.rtt <- AggregateDataPP(cumulative.payments.triangle=sifa.mtpl)
hz.chl=clmplus(sifa.mtpl.rtt, 'a')

clmplus documentation built on Aug. 8, 2025, 6:06 p.m.