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Wind speed prediction analysis using Rayleigh distribution

Abstract

Two parameter Rayleigh distribution is considered for prediction analysis of quantiles at extreme upper and lower tail areas of the distribution. Four methods of estimation of the parameters namely, probability weighted moment (PWM), method of maximum likelihood (MLE), method of moment (MM), and ordinary least square method (OLS) are illustrated. The Rayleigh distribution is fitted to monthly averages and monthly maximum wind speed data in Oman by each of these four estimation methods. Theoretical quantiles at various probabilities were estimated by each of these method and were compared with empirical quantiles. The mean absolute error (MAE) and mean squared errors (MSE) of the fit due to each method were worked out. It is concluded that the two parameter Rayleigh distribution can best be fitted by probability weighted moment (PWM) method.

Wind Energy Research and DevelopmentWind and Air Flow StudiesAerodynamics and Fluid Dynamics ResearchMathematicsRayleigh distributionQuantileStatisticsMoment (physics)Mean squared errorOrdinary least squaresProbability density function
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Wind speed prediction analysis using Rayleigh distribution · Scinovex