Model sensitivity

My current search for model improvements (however small) has focussed in part on assessing how a number of statistically equivalent models behave when applied to estimating handicap numbers.  In particular, the sensitivity of results when the input data has some inaccuracy can point to the type of model components contributing to making a model robust. 

Clearly, the effectiveness of any model relies on the accuracy of input data.  Article 2.5 states the accuracy needed in the required ‘brochure’ measurements.  To date, the most efficient models require extra information about foresail area and this may involve user measurements and estimation.  Newly added here is Article 2.9  which discusses this issue, and articles 2.5 onwards have links with 2.9.