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Qu'est-ce (qui) est credibility$17524$ - définition

Actuarial credibility; Credibility Theory

Credibility theory

Credibility theory is a form of statistical inference used to forecast an uncertain future event developed by Thomas Bayes. It is employed to combine multiple estimates into a summary estimate that takes into account information on the accuracy of the initial estimates.

https://en.wikipedia.org/wiki/Credibility_theory

Credibleness

BELIEVABILITY OF A SOURCE OR MESSAGE, COMPRISING OBJECTIVE AND SUBJECTIVE COMPONENTS

Cred; Street Cred; Credible; Street-cred; Street cred; Incredibility; Street credibility; Credibilities; Credibleness; Scientific credibility; Believability; Credibly

·noun The quality or state of being credible; worthiness of belief; credibility.

street credibility

BELIEVABILITY OF A SOURCE OR MESSAGE, COMPRISING OBJECTIVE AND SUBJECTIVE COMPONENTS

Cred; Street Cred; Credible; Street-cred; Street cred; Incredibility; Street credibility; Credibilities; Credibleness; Scientific credibility; Believability; Credibly

Street credibility is the same as street cred
. (mainly BRIT)

N-UNCOUNT

Wikipédia

Credibility theory

Credibility theory is a branch of actuarial mathematics concerned with determining risk premiums. It is employed to combine multiple estimates into a summary estimate that takes into account information on the accuracy of the initial estimates. For example, in group health insurance an insurer is interested in calculating the risk premium, $RP$ , (i.e. the theoretical expected claims amount) for a particular employer in the coming year. The insurer will likely have an estimate of historical overall claims experience, $x$ , as well as a more specific estimate for the employer in question, $y$ . Assigning a credibility factor, $z$ , to the overall claims experience (and the reciprocal to employer experience) allows the insurer to get a more accurate estimate of the risk premium in the following manner:

The credibility factor is derived by calculating the maximum likelihood estimate which would minimise the error of estimate. Assuming the variance of

x

and

y

are known quantities taking on the values

u

and

v

respectively, it can be shown that

z

should be equal to:

Therefore, the more uncertainty the estimate has, the lower is its credibility.

https://en.wikipedia.org/wiki/Credibility theory