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Technical resources for implementing the measurement, reporting and verification arrangements under the Convention and the enhanced transparency framework under the Paris Agreement.




Ideally, you should identify the probability density function (PDF) of each individual variable, then run the simulations based on the variable, and then combine the simulations to identify the final distribution of the variable in question. You should only make assumptions about the distribution when you do not have access to the underlying dataset. If this is the case, then you have to make educated assumptions about the data. There is extensive literature on the distribution of tree sizes, so you could research studies on this topic focusing on the geographic region and forest type of interest to come up with the reasonable probability density function. Because it is a natural phenomenon, one could assume that the distribution is normal. This, however, is a broad assumption, and it is better to verify with an actual distribution fit to a PDF using a goodness of fit test or through scientific literature review.
(Anna McMurray, Winrock  International)


In step 1 of the Monte Carlo approach, which distribution would you use when it comes to combined variables, such as. i.e. tree dbh's that are either in forest or non-forest. Individually they may be normal, but their interaction may not be


Created at 29/05/2018 15:39 by Bhava Dhungana
Last modified at 29/05/2018 15:39 by Bhava Dhungana