Coerce experience data to a Total object — as

Validate raw experience data, aggregate it to a single scalar row per group (collapsing both the cohort and development axes), and assign the Total S3 class so the associated plot.Total() bar chart and other Total methods dispatch on the result.

Compared with as_triangle() (two-dimensional cohort x dev) and as_calendar() (one-dimensional time series), as_total() is zero-dimensional per group – one row of portfolio aggregates. The typical use is high-level portfolio comparison across products, coverages, or channels.

Total summarises:

the number of observed cohorts (n_cohorts)
the first and last observed cohort periods (sales_start, sales_end)
total loss and total premium (sum over all cells)
total loss ratio (ratio = loss / premium)
each group's share of total loss and total premium

Pre-filter the Triangle (e.g. by cohort range or coverage) before calling as_total() if a subset summary is needed.

Usage

as_total(x)

Arguments

x: A Triangle object (typically from as_triangle()).

Value

A data.frame with class "Total" containing:

n_cohorts: Number of observed development periods
sales_start: First observed period
sales_end: Last observed period
loss: Total loss
premium: Total premium
ratio: Total loss ratio (loss / premium)
loss_share: Share of total loss
premium_share: Share of total premium

Examples

if (FALSE) { # \dontrun{
tri <- as_triangle(
  experience,
  groups   = "coverage",
  cohort   = "uy_m",
  calendar = "cy_m",
  loss     = "incr_loss",
  premium  = "incr_premium"
)
as_total(tri)
} # }