A. Kozak, EFFECTS OF MULTICOLLINEARITY AND AUTOCORRELATION ON THE VARIABLE-EXPONENT TAPER FUNCTIONS, Canadian journal of forest research, 27(5), 1997, pp. 619-629
Effects of multicollinearity, autocorrelation and two sampling strateg
ies were studied on two new variable-exponent taper equations using Mo
nte Carlo simulations. These two equations were derived from Kozak's 1
988 model. Results of the study indicated that predictions are unbiase
d even if the taper model has severe multicollinearity and autocorrela
tion. On the other hand, the estimations are considerably more variabl
e when severe multicollinearity exists. The use of single observations
per tree (uncorrelated errors) does not improve the predictive abilit
y of the functions. Taper functions based on a uniform selection of sa
mple trees predict the response variables well, but provide poorer est
imates of the parameters than random selection.