A test of nonparametric smoothing of diameter distributions
- 1 January 1989
- journal article
- research article
- Published by Taylor & Francis in Scandinavian Journal of Forest Research
- Vol. 4 (1-4) , 407-415
- https://doi.org/10.1080/02827588909382577
Abstract
Smoothing a sample‐based diameter distribution can provide a potentially better paradigm of a population distribution. Goodness‐of‐fit comparisons between raw cumulative distribution functions, nonparametric curves and Weibull densities fit to the raw distribution are presented based on two simulated forest stands.Keywords
This publication has 15 references indexed in Scilit:
- A nonparametric technique for taper function estimationCanadian Journal of Forest Research, 1985
- Averaged Shifted Histograms: Effective Nonparametric Density Estimators in Several DimensionsThe Annals of Statistics, 1985
- Frequency Polygons: Theory and ApplicationJournal of the American Statistical Association, 1985
- Monte Carlo Study of Three Data-Based Nonparametric Probability Density EstimatorsJournal of the American Statistical Association, 1981
- Choosing the window width when estimating a densityBiometrika, 1978
- Kernel density estimation revisitedNonlinear Analysis, 1977
- On the Choice of Smoothing Parameters for Parzen Estimators of Probability Density FunctionsIEEE Transactions on Computers, 1976
- Non-Parametric Estimation of a Multivariate Probability DensityTheory of Probability and Its Applications, 1969
- On Estimation of a Probability Density Function and ModeThe Annals of Mathematical Statistics, 1962
- Remarks on Some Nonparametric Estimates of a Density FunctionThe Annals of Mathematical Statistics, 1956