reserving.MackBootstrapFit
A fitted bootstrap of Mack’s model, the lifetime view, of every
Usage
reserving.MackBootstrapFit()segment (MackBootstrap.fit).
reserves is one joint distribution with the triangle’s keys and "origin" as dimensions, so reserves.aggregate(["lob"]) keeps the dependence between segments. Per-origin lists run over the origins of each segment in turn, like the rows of to_frame() and the components of reserves. residuals needs a single-segment fit; for several segments use segment(...).
Attributes
| Name | Description |
|---|---|
| chain_ladder | The chain ladder of Mack’s model (its averaging): the reserves the |
| development | Development ages in months. |
| index | Label of each segment, as Triangle.index. |
| keys | Names of the triangle’s key columns; empty without keys. |
| mack | Mack’s model on the observed triangle, without a tail: the factors |
| origins | Origin period of each per-origin value and reserve component. |
| reserves | Joint distribution of the reserve (each origin’s last simulated |
| residuals | Mack’s scaled bias-adjusted residuals of the link ratios, |
chain_ladder
The chain ladder of Mack’s model (its averaging): the reserves the
chain_ladder: ChainLadderFit
bootstrap’s mean equals with centre_residuals=True, the default.
development
Development ages in months.
development: list[int]
index
Label of each segment, as Triangle.index.
index: list[Any]
keys
Names of the triangle’s key columns; empty without keys.
keys: list[str]
mack
Mack’s model on the observed triangle, without a tail: the factors
mack: MackFit
and sigmas the simulation uses, and the analytic standard errors the simulated standard deviations approximate.
origins
Origin period of each per-origin value and reserve component.
origins: list[str]
reserves
Joint distribution of the reserve (each origin’s last simulated
reserves: PredictiveDistribution
cumulative value less its latest) by segment and origin: the triangle’s keys and "origin" are its dimensions, one component per segment and origin, one row per simulation. Its mean and quantile describe the total reserve. Columns of draw_matrix() follow origins.
residuals
Mack’s scaled bias-adjusted residuals of the link ratios,
residuals: list[list[float]]
[origin][development], [o][k] the link from age k to k + 1; nan where there is none, from a zero, or behind a factor with a single link ratio or a zero sigma. Never centred.
Methods
| Name | Description |
|---|---|
| development_frame() | The chain ladders’ development factors, one row per segment and |
| segment() | The bootstrap of one segment, chosen by key values as |
| to_frame() |
One row per segment and origin: the key columns, origin, the
|
| totals_frame() | One row per segment: the key columns, the chain ladder’s totals, and |
development_frame()
The chain ladders’ development factors, one row per segment and
Usage
development_frame()age, as ChainLadderFit.development_frame. Needs pandas.
Returns
pandas.DataFrame
segment()
The bootstrap of one segment, chosen by key values as
Usage
segment(**keys)ChainLadderFit.segment, with its part of the joint reserves (same dimensions).
Returns
MackBootstrapFit
to_frame()
One row per segment and origin: the key columns, origin, the
Usage
to_frame()chain ladder’s latest, ultimate and reserve, and the mean and std_dev of the bootstrapped reserve. Needs pandas.
Returns
pandas.DataFrame
totals_frame()
One row per segment: the key columns, the chain ladder’s totals, and
Usage
totals_frame()the mean and std_dev of the segment’s bootstrapped total reserve. Needs pandas.
Returns
pandas.DataFrame