The parallel application of two probability models, logit and probit, for the accurate analysis of spruce timber damage due to thinning operations
[ 1 ] Instytut Matematyki, Wydział Elektryczny, Politechnika Poznańska | [ P ] employee
2016
scientific article
english
- generalised linear models
- categorical data
- goodness of fit
- akaike criterion
EN Logit and probit models belong to the class of generalised linear models. A few applications of both models have been documented in the field of forestry. The objective of this paper was to test the parallel use of these models to discover the differences in damage to a spruce stand after thinning using the full tree system, the long wood system and the short wood system. In particular the aim was to ascertain the general damage probability caused by the harvesting systems (HS) and the particular damage class probability in each HS. When the general damage probability was calculated the logit model was used. When nine damage classes were taken into account, however, the probit model was found to fit the data better. In this case, the results obtained gave accurate information on the probability of the appearance of a particular damage class for each HS. It was concluded that the probit and logit models should be considered in parallel in order to obtain the best possible goodness of fit and to get accurate information on the distribution of damage classes.
49 - 59
CC BY (attribution alone)
open journal
final published version
public
15
0,642