Scanning the effect of a partial adjustment

For the second form of the syntax we assume that an adjustment has already taken place. We will assume that the collection to be adjusted is the base B, and that the currently fitted collections can be arranged as the collection D. Hence, we assume the scenario that would result if we issued the command

BD>adjust : [ B / D ]

It is also possible to use this second form of the syntax for the SCAN:  command when a collection has been prepared for adjustment using either of the following two ways:

BD>adjust : [ B / ]

BD>scan : [ B / ]

in which case there is no current fit, and for the purposes of this section we will assume that D is empty. However, in such scenarios it would be more natural to use the first form of the syntax described above.

The action of the SCAN:  command is now to evaluate limited aspects of the partial adjustment of the base B by the base F, having already adjusted by the base D. That is, the potential of the further adjustment by is assessed. The following information is available after such a command has been issued.

• the system adjustment uncertainty (essentially the standardised uncertainty remaining in the collection B having adjusted by both D and F), is stored in the operand scurvar . In the notation of [31, page 13,], the quantity stored is .
• For each pair of elements in the base B, say, we store their adjusted covariance,

  

  This then can be accessed via the [B/D] operator scac  as scac  analagously to the [B/D] operator ac . For adjusted variances, we could also use the scav  operator in that scav  is equivalent to, and shorthand for, scac 

• By setting the scac  control to some valid belief store, the potential adjusted variance-covariance matrix may also be directed to a belief store. Every time the SCAN:  command is issued, the adjusted covariances are then output to this belief store. This facility works independently of the availability of the adjusted covariances via the scac  operator.
• For each element in the base B, we store the adjusted expectation,

  

  This then can be accessed via the [B/D] operator scae  as scae  analagously to the [B/D] operator aex .

• By setting the scae  control to some valid expectation store, the potential adjusted expectation vector may also be directed to an expectation store. Every time the SCAN:  command is issued, the adjusted expectations are then output to this store. This facility works independently of the availability of the adjusted covariances via the scae  operator.

As an example, consider the fragment of code given in Figure 9.4. Here, we scan for the effect of adjusting B by D and then some other base F. Assume that the base B contains elements X, Y, and Z. To begin, we switch off the scac  control, so that we don't copy the adjusted covariances to a belief store for this and subsequent SCAN:  commands. This is followed by the SCAN:  command itself, and then various lines of output which show how we access the results of the command.

 
Figure 9.4:  Scanning partial adjustments

Similar information to this (albeit in terms of resolutions) can be obtained by using the arcin  operator following an adjustment.