DIGITALNA ARHIVA ŠUMARSKOG LISTA

prilagođeno pretraživanje po punom tekstu

ŠUMARSKI LIST 10-11/1974 str. 17 <-- 17 --> PDF |

Summary EXAMPLE FOR ELECTRONIC DATA PROCESSING BY THE METHOD OF STEPWISE REGRESSION During 1970 were taken measurements of some characteristics in the progeny test of European Larch on the experimental plot »Goić« near Jastrebarsko. Data of measurement served as a material for the computation and finding of a multiple linear equation as suitable as possible, using various working techniques in the method of multiple stepwise regression. As a dependent variable (y) the height of tree is used, and as independent variables (x) the following characteristics: diameter b. h., number of branches per 1 m of length, diameter of the thickest branch in the mid-crown, length of the thickest branch, diameter in the mid- crown, insertion angle of branches and straightness of the stem. All computations were performed on an IBM-computer of the Institute for Statistics, North Carorolina University at Raleigh, USA, in 1971. In finding out the most favourable linear equation by the method of multiple stepwise regression the following working techniques were used: forward selection, backward elimination, stepwise, maximum R-square improvement and minimum R-square improvement. The method of multiple stepwise regression gave a very good insight into the relations between the dependent variables and the independent ones, and into the mutual relations within the independent variables (correlation coefficients). Although this method is complicated when a great number of independent variables are included into the model, the computations are much easier than when the method of all possible regression equations is used. The number of combinations in this method amounts to 2n. What working technique to use in applying the method of multiple gradual regression is best lo leave to the user, for all of them have their advantages and drawbacks. However, it ought to be stated that in applying by means of the maximal and minimal determination coefficient (R4) almost always the same equation should be selected. In conclusion, it should be stated that the aim of this paper is to present certain possibilities for using modern electronic systems in data processing by means of methods of multiple regression, in the selection of the necessary number of independent variables, disregarding the theoretical consideration of the problem itself. |