A very common practice in forest modelling is to summarise diameter distribution data through use of probability density functions. By far the most popular model is the Weibull which, as well as being versatile, has the distinct advantage that its parameters are readily estimable. In practice, the location parameter a is usually equated to a minimum (sample) value. The scale and shape parameters are estimated iteratively or (approximately) explicitly, through use of moments or percentiles. Here, we expand and develop the use of moments to estimate all three parameters; the essential enhancement is that information concerning the distribution asymmetry is utilised, via the sample skewness statistic. Normally, this information is ignored. Applying the methodology to a Pinus radiata dataset showed that the goodness of fit was improved on average by 15%. On modern computers the method is easily and quickly assayed, so its usage is recommended. There are grounds for suggesting that the method could be embedded in diameter distribution growth-and-yield systems to good effect.
|Number of pages||5|
|Journal||Forest Ecology and Management|
|Publication status||Published - 1996|
- Diameter distribution prediction
- Method of moments estimation
- Skewness information