Parameters Estimation of Nakagami Probability Distribution Using Methods of L.Moments
DOI:
https://doi.org/10.24949/njes.v8i1.150Abstract
In communications theory, Nakagami distribution (NKD) is used to model scattered signals that reach a receiver from different paths. In order to use NKD to model a given set of data, we will have to estimate its parameters from the given data. Method of L-Moments (MLM) is being compared with Method of Moments (MOM) for estimating the parameters of NKD. In this study, we have derived its first two L-moments in closed form and estimated its parameters using simulated data. This study shows that estimates based on MLM are better than MOM, not only in small samples but also in large samples. For evaluation purpose, we calculated Root Mean Square Error (RMSE) and Bias using Monte Carlo simulations.
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