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<noinclude>[[Category:United States state templates]]</noinclude> to the end of the template code, making sure it starts on the same line as the code's last character. This is a collection of the primary information templates for each state/territory in the United States , and also templates relating specifically to the U.S. states.
The calculation of expected losses utilizes past audited payroll information for a particular employer, by classification code and state. These payrolls are multiplied by Expected Loss Rates, which are calculated by rating bureaus based on past reported claims costs per classification.
This is the template test cases page for the sandbox of Template:Ohio road map to update the examples. If there are many examples of a complicated template, later ones may break due to limits in MediaWiki; see the HTML comment "NewPP limit report" in the rendered page. You can also use Special:ExpandTemplates to examine the results of template uses. You can test how this page looks in the ...
English: Map of US states and Washington, D.C. letting editors easily populate data. By CMG Lee.The base map is from Blank US Map (states only).svg.This map is called a template map because it can be used to make more US maps easily.
The costate variables () can be interpreted as Lagrange multipliers associated with the state equations. The state equations represent constraints of the minimization problem, and the costate variables represent the marginal cost of violating those constraints; in economic terms the costate variables are the shadow prices.
An increased limit factor (ILF) at limit L relative to basic limit B can be defined as = + + + + + + ()where ALAE is the allocated loss adjustment expense provision, ULAE is the unallocated loss adjustment expense provision, and RL is the risk load provision.
The Cost-loss model considers one forecast prior to an event, while the Extended cost-loss model considers two forecasts at different times prior to the event. The Extended cost-loss model is an example of a dynamic decision model, and links the cost-loss model to the Bellman equation and Dynamic programming.
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