ILD

(redirected from Internal Loss Data)
AcronymDefinition
ILDInterstitial Lung Disease
ILDInnovative Lighting Design (various locations)
ILDIch Liebe Dich (German: I Love You)
ILDIlluminations Lighting Design (Texas)
ILDInternational Long Distance
ILDInteger Load
ILDInternet Listing Display
ILDInternational Leisure Development (consortium)
ILDInstitute for Liberty and Democracy (Peru)
ILDInternational Leak Detection (various locations)
ILDIndentation Load Deflection (foam firmness testing)
ILDInstructional Leadership
ILDInternational Labor Defense
ILDInternational Literacy Day (UNESCO)
ILDInjection Laser Diode
ILDInter Layer Dielectric
ILDInternational Lunar Decade (astronomy)
ILDInter-Level Dielectric
ILDInternational Leadership Development
ILDI Love Dogs
ILDInstitute for Leadership Development
ILDInductive Loop Detector
ILDInsertion Loss Deviation
ILDInternational Large Detector (physics)
ILDInter Laminar Decompression (spinal surgery)
ILDInter Aural Time Delay
ILDInitial Load Deflection (mattress firmness)
ILDInstrument Loop Diagram
ILDInternal Loss Data
ILDI Like Dirt (song title)
ILDInternal Locking Device
ILDIntraline Distance (explosives)
ILDIndex-Linked Deposit
ILDIntegrated Logistics Design (various locations)
ILDInitial Launch Data
ILDInstitutional Learning and Documentation
ILDImproved Landmine Detection
ILDIndependent Layout Delivery
References in periodicals archive ?
For implementing AMA there are certain steps that should be taken and the first step is to maintain the database of internal loss data for at least 3 years.
Continuing with the example of a $20 million loss whose frequency is once in 10 years, in order to merge this scenario with internal loss data from 5 years' experience, we will have to consistently recreate internal data with a sample size equivalent to a period of 10 years.
From preliminary research, we have undertaken on external data, we are not comfortable using our approach on units of measure that have insufficient internal loss data to develop a meaningful and stable model.
This choice is consistent with the continuous distributions we use for modeling the severity of internal loss data.
i] is the number of losses observed annually, sampled from the frequency distribution of the internal loss data for that particular unit of measure.
Assumption 1: During a short and reasonably specified period of time, such as 1 year or less, the frequency and severity distributions based on the internal loss data for a unit of measure do not change.
Our analysis does not use scenario data as a substitute for internal loss data.
In our experiments, however, probabilities based on internal loss data have proved to be much more stable than those based on both internal and external loss data.
Discussion of the choice and appropriateness of a distribution for fitting the internal loss data is beyond the scope of this work.
Table 1 shows the results of goodness-of-fit tests for five distributions used to model the internal loss data for a particular unit of measure at a financial institution.
Any of the five distributions could be used to model the internal loss data.
In that sense, loglogistic has the best predictive power for the given set of scenarios, conditional on the internal loss data.
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