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  1. Size-biased distributions in the generalized beta distribution family, with applications to forestry

    Size-biased distributions arise in many forestry applications, as well as other environmental, econometric, and biomedical sampling problems. We examine the size-biased versions of the generalized beta of the first kind, generalized beta of the second kind and generalized gamma distributions. These distributions include, as special cases, the Dagum (Burr Type III),...

    https://www.fs.usda.gov/treesearch/search?keywords=%22Generations%22&%3Bf%5B0%5D=year%3A%222019%22&f%5B0%5D=author_facet%3A%22Hse%2C%20Chung-Yun%22&f%5B1%5D=author_facet%3A%22Wolf%2C%20Kathleen%22&f%5B2%5D=author_facet%3A%22Alerich%2C%20Carol%22&f%5B3%5D=author_facet%3A%22Zipperer%2C%20Wayne%20C.%22&f%5B4%5D=author_facet%3A%22Flebbe%2C%20Patricia%22&f%5B5%5D=author_facet%3A%22Pincetl%2C%20Stephanie%22&f%5B6%5D=author_facet%3A%22Gove%2C%20Jeffrey%22

    Author(s):
    Mark J. Ducey; Jeffrey H. Gove
    Year:
    2015
    Keywords:
    Source:
    Forestry. 88(1): 143-151.

  2. The unbiasedness of a generalized mirage boundary correction method for Monte Carlo integration estimators of volume

    The typical "double counting" application of the mirage method of boundary correction cannot be applied to sampling systems such as critical height sampling (CHS) that are based on a Monte Carlo sample of a tree (or debris) attribute because the critical height (or other random attribute) sampled from a mirage point is generally not equal to the critical...

    https://www.fs.usda.gov/treesearch/search?keywords=%22Generations%22&%3Bf%5B0%5D=year%3A%222019%22&f%5B0%5D=author_facet%3A%22Hse%2C%20Chung-Yun%22&f%5B1%5D=author_facet%3A%22Wolf%2C%20Kathleen%22&f%5B2%5D=author_facet%3A%22Alerich%2C%20Carol%22&f%5B3%5D=author_facet%3A%22Zipperer%2C%20Wayne%20C.%22&f%5B4%5D=author_facet%3A%22Flebbe%2C%20Patricia%22&f%5B5%5D=author_facet%3A%22Pincetl%2C%20Stephanie%22&f%5B6%5D=author_facet%3A%22Gove%2C%20Jeffrey%22

    Author(s):
    Thomas B. Lynch; Jeffrey H. Gove
    Year:
    2014
    Keywords:
    critical height sampling, importance sampling, Monte Carlo integration
    Source:
    Canadian Journal of Forest Research. 44(7): 810-819.

  3. The ssWavelets package

    This package adds several classes, generics and associated methods as well as a few various functions to help with wavelet decomposition of sampling surfaces generated using sampSurf. As such, it can be thought of as an extension to sampSurf for wavelet analysis.

    https://www.fs.usda.gov/treesearch/search?keywords=%22Generations%22&%3Bf%5B0%5D=year%3A%222019%22&f%5B0%5D=author_facet%3A%22Hse%2C%20Chung-Yun%22&f%5B1%5D=author_facet%3A%22Wolf%2C%20Kathleen%22&f%5B2%5D=author_facet%3A%22Alerich%2C%20Carol%22&f%5B3%5D=author_facet%3A%22Zipperer%2C%20Wayne%20C.%22&f%5B4%5D=author_facet%3A%22Flebbe%2C%20Patricia%22&f%5B5%5D=author_facet%3A%22Pincetl%2C%20Stephanie%22&f%5B6%5D=author_facet%3A%22Gove%2C%20Jeffrey%22

    Author(s):
    Jeffrey H. Gove
    Year:
    2017
    Keywords:
    Source:
    28 p. http://sswavelets.r-forge.r-project.org/

  4. The Chapman-Richards Distribution and its Relationship to the Generalized Beta

    Background: The Chapman-Richards distribution is developed as a special case of the equilibrium solution to the McKendrick-Von Foerster equation. The Chapman-Richards distribution incorporates the vital rate assumptions of the Chapman-Richards growth function, constant mortality and recruitment into the mathematical form of the distribution....

    https://www.fs.u