Abstract
We wish to present a method to quantify the value modifying effects when comparing animal farms. To achieve our objective, multi-variable statistical methods were needed. We used a principal component analysis to originate three separate principal components from nine variables that determine the value of farms. A cluster analysis was carried out in order to classify farms as poor, average and excellent. The question may arise as to which principal components and which variables determine this classification.After pointing out the significance of variables and principal components in determining the quality of farms, we analysed the relationships between principal components and market prices. Some farms did not show the expected results by the discriminant analysis, so we supposed that the third principal component plays a great role in calculating prices. To prove this supposition, we applied the logistic regression method. This method shows how great a role the principal components play in classifying farms on the basis of price categories.
Highlights
We present a method to quantify the value modifying effects when comparing animal farms
We carried out a cluster analysis on these results
We wanted to know whether the mechanical classification of the farms fits to that realised in the cluster analysis
Summary
We wish to present a method to quantify the value modifying effects when comparing animal farms. We used a principal component analysis to originate three separate principal components from nine variables that determine the value of farms. Some farms did not show the expected results by the discriminant analysis, so we supposed that the third principal component plays a great role in calculating prices. To prove this supposition, we applied the logistic regression method. This method shows how great a role the principal components play in classifying farms on the basis of price categories. We present a method to quantify the value modifying effects when comparing animal farms. The PC 3 only consists of the seed-crop variable, so it is appropriate
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have