B.10.Brosius
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Table M  Construction Data Requirement
 sample of experience from grp of similarly sized risks (loss dist varies by size of risk)
 aggregate ELR (can use sample mean)

Table M  Insurance charge φ(r)
 area above r in Lee Diagram / total area
 when we need only 1, limit r to what we're interested in, φ(r) = avg diff btwn lim / unlim

Table M  Vertical slice method
 look risk by risk
 (+) natural approach  as data is presented
 (+) easiest to understand
 (+) quick for 1 entry ratio
 () need to repeat entire process for other r's
 () need to deal w each risk individually

Table M  Horizontal slice method
 look by layer
 (+) easiest to compute more than one ins charge
 () difficult to understand
 () initial prep work is needed in most cases

Table M  Construct w horizontal method
 φ(r) = width * % risks over
 φ(r) = r_{i+1}  r_{i} * # risks over / total # risks

Table M  If μ ≠ sample mean
 theory: use sample mean
 practice: use μ and normalize table (divide all by φ(0))