For example, I've had an example where factor 1 would classify low resolution parameters and factor 2 and further are the only factors of relevance.
When one examined the data, some parameters were in 40 square kilometer boxes and others in more like 0.5 square kilometer boxes. Factor 1 would tell you which parameters are in the 40 square kilometer boxes.
Another interesting example is that one can use this to for example counteract the effects of inflation on sales prices.
When one examined the data, some parameters were in 40 square kilometer boxes and others in more like 0.5 square kilometer boxes. Factor 1 would tell you which parameters are in the 40 square kilometer boxes.
Another interesting example is that one can use this to for example counteract the effects of inflation on sales prices.