Bayesian calibration
Model parameters are calibrated with Bayesian methods that combine prior knowledge with data and produce posterior distributions, including a term for model discrepancy.
GCRI · Zanista pergalan û modelkirin
Statistics for modelling
Probability and statistics are the language of uncertainty in modelling. In this field they underpin calibration, inference about parameters, evaluation of model performance and the honest reporting of ranges, for every modelling platform in the network.
01Qeyd
Statistics for modelling on the record.
Method recordSTEM method
- RêbazÎhtîmal û statîstîk
- ParêzvanPergal û modelkirin
- Applied inZanista pergalan û modelkirin
- Dane3 inputs
- Checks3 validation steps
- Canonical pageSTEM Commons
02Application
What probability and statistics does here.
Probability and statistics provide the mathematical framework for describing uncertainty and learning from data. They underpin estimation, testing and prediction in every risk discipline. In methods and modelling, risk management and xetera pergalî and research and evidence, statistical methods quantify the likelihood and uncertainty of losses across interconnected pergalan. They make the evidence behind risk decisions explicit and reproducible. The canonical description is on STEM Commons.
Proper scoring of predictions
Probabilistic model outputs are scored with proper scoring rules so that honest uncertainty is rewarded.
Ensemble statistics
Ensembles of model runs are summarised with statistical methods that account for dependence between ensemble members.
03Rêbaz û delîl
How statistics for modelling is modelled, measured and tested.
Model, texmînên wî, daneyên wî û nediyariya wî, bi şeweyê ku zanyar an endezyar kontrol bike. Avahî rêbazên weşandî dişopînin. Nirxên hatine xêzkirin nimûneyî ne, ne encam in.
Model, hevkêşe û texmîn
The model structure used for statistics for modelling, the assumptions it makes and how each is tested.
Xetera hêmana i
Ri = f(Hi, Ei, Vi, Ci)metirsî, rûbirûbûn, lawazî û kapasîteya serederiyêWindahiya salane ya hêvîkirî
EAL = ∑k pk · Lkli ser bûyerên k bi îhtîmala salane pkPergalên girêdayî
xt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error| Texmîn | Çima tê çêkirin | Çawa tê ceribandin |
|---|---|---|
| Metirsî û rûbirûbûn di nav bûyerekê de serbixwe ne | Entegrala windahiyê ji hesabkirinê re maqûl dihêle | Bi lihevhatineke copula li ser tomarên hevbeş re bidin ber hev |
| Girêdan li nêzî xala xebatê xêzik in | Dihêle şok di A de belav bibin | Ji derveyî rêza xêzik tevlihev bike û bide ber hev |
| Xêzên lawaziyê di navbera cihan de têne veguhastin | Xêzikên herêmî kêm tên dîtin | Li hember windahiyên çavdêrîkirî erê bike li cihê ku hene |
- Têketin
- danehevên bi guhertoyan û çavkaniyê
- Derketin
- belavkirin, tu carî jimarên tenê
- Kod
- bi qerta modelê û ceribandinan re hat weşandin
- Zêdebûn
- heman dane, kod, jîngeh û tov
Prensîbên rêber ên FAIR · GO FAIR û FORCE11W3C PROV · World Wide Web ConsortiumRêwerzên ji bo birêvebirina hevgirtî ya nediyarîyan · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
04Dane
What the method consumes.
Datasets and records used by probability and statistics on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Dane | Rol | Nîşan |
|---|---|---|
| Observational datasets | Calibration and evaluation | ÇAVDÊRÎKIRÎ |
| Model ensemble outputs | Statîstîk | MODELKIRÎ |
| Prior information from literature | Bayesian priors | REPORTED |
05Pêvajo
Pêvajo çawa dimeşe.
Process explorer · Process
Statistics for modelling: Catastrophe model pipeline
10 steps·5 qonax
Pêvajo
Statistics for modelling: Catastrophe model pipeline
Catastrophe models usually have hazard, vulnerability, exposure and financial modules, and produce loss tables, windahiya salane ya navînî, exceedance curves, PML and TVaR.
01 Hazard
- 01Event catalogueDataset · Model developerThe hazard module holds a large catalogue of simulated events that represents a wide range of plausible scenarios.
- 03Hazard moduleModel · Model developerFor each event the hazard module gives the local hazard intensity that the vulnerability module reads.
02 Exposure and damage
- 02RûbirûbûnDataset · Validation reviewerThe exposure module houses the portfolio data, such as location-specific information.
- 04Vulnerability moduleModel · Model developerThe vulnerability module quantifies the expected damage to the exposures from an event.
03 Financial
- 05Financial moduleModel · Validation reviewerThe financial module calculates losses from all event scenarios. Ground-up, gross and net losses differ as shown below.
- 06Event loss tableDataset · Validation reviewerAn event loss table lists each event with its annual occurrence probability and its loss for the portfolio.
- 07Year loss tableDataset · Validation reviewerSome models also sample simulated years from event losses. This outline does not describe their format.
04 Metrics
- 08Exceedance probability curvesModel · Validation reviewerThe occurrence curve gives the chance that the largest loss in a year exceeds an amount. The aggregate curve does so for the sum of losses.
- 09AAL, PML and TVaRModel · Validation reviewerAverage annual loss sums event probability times loss. PML is one point on the occurrence curve.
05 Use of results
- 10Use of resultsDecision · Validation reviewerThe tail metrics are used when considering a portfolio’s exposure and the level of catastrophe reinsurance an insurer requires.
Outline of an external standard or method, from its public sources. It describes what the framework says, not a record of any run. It does not show that Nexus or any partner performs, certifies or approves a step. A gate is a step of the method, never a Nexus approval.
06Erêkirin
How results are checked.
Results are checked through diagnostics, cross-validation and sensitivity to assumptions. Independent replication confirms findings.
| Kontrol bikin | How it is done |
|---|---|
| Posterior predictive checks | Calibrated models must reproduce observed data |
| Prior sensitivity | Results are recomputed under alternative priors |
| Scoring on held-out data | Predictions are scored on data not used in calibration |
Inference depends on assumptions about independence, distribution and sampling that may not hold. Small or biased samples limit reliability.
07Connections
Topics that rely on this method.
08Stewardship
Who maintains the method.
Pergal Science and Modelling stewards probability and statistics for the Consortium and reviews how it is applied across platforms.
09Pirs
Pirs û bersiv.
What are the limits of probability and statistics in this field?
Inference depends on assumptions about independence, distribution and sampling that may not hold. Small or biased samples limit reliability.
How are results checked?
Results are checked through diagnostics, cross-validation and sensitivity to assumptions. Independent replication confirms findings.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
Çavdêrxaneya canonical method page lists every platform that applies it.
rêzeya Pergalên StratejîkTevkarî bike
Ji vê rûpelê delîl bidin.
rêzeya Pergalên Stratejîk is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
GCRIZanista pergalan û modelkirinRêbaz û teknîkîSenaryo û ceribandina stresê
- E-nameDergeh GW-GCRIJi vê rûpelê bişîninDelîl, rastkirin, doz, rêbaz, nirxandin, wergerandin an têketina profîlê. Bi nîşana vê rûpelê digihîje, ji ber vê yekê edîtorê xwediyê wê wê bistîne.
- ZenodoDepoya vekirîWê razînin û ji civakê re bişîninTomara xwe li Zenodo bi ORCID iD ya xwe biweşînin, paşê wê li wir ji civaka Reports re bişînin. Kurator wê vedikolin; DOI ya we dimîne.
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Zanista pergalan û modelkirin
Rêbazek, danehevek an pirsek bîne.
Agahî û pirs îro vekirî ne. Pirsek referansekê distîne û gava piştî wê dide nasîn; serlêdan, drav, veqetandina hesabkirinê û tomarkirin tenê dema ku tîm, mercên wê û kapasîteya vekolînê hebin vedibin.
Hiqûqî
Belgeyên hiqûqî.
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