Data truncation is a commonly accepted method of dealing with initialization bias in discrete-event simulation. An algorithm for determining the appropriate initial-data truncation point for ...
Doubly truncated data arise when the variable of interest is observable only if it falls between pre‐specified lower and upper bounds. This phenomenon poses significant challenges to statistical ...
Typically, operational risk losses are reported above some threshold. This paper studies the impact of ignoring data truncation on the 0.999 quantile of the annual loss distribution for operational ...
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