Extract the Weibull coefficients

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Armel
Armel el 24 de Oct. de 2022
Comentada: Armel el 25 de Oct. de 2022
Hello,
I have an excel with wind data (for the purpose of dimensioning a wind farm) over a full year with a reading at each quarter hour. I would like to extract the Weibull coefficients from this data in order to plot the distribution.
Is there a MatLab function to do this? Or another technique?
Thank you very much in advance.

Respuesta aceptada

John D'Errico
John D'Errico el 24 de Oct. de 2022
Editada: John D'Errico el 24 de Oct. de 2022
When you don't know what the name of a function in MATLAB might be, use the lookfor function.
lookfor weibull
networkTrafficVideoConference.WeibullScale - Scale parameter for Weibull distribution networkTrafficVideoConference.WeibullShape - Shape parameter for Weibull distribution surfaceReflectivityCustom.SpeckleScale - Scale parameter for Weibull and Rayleigh speckle distribution surfaceReflectivityCustom.SpeckleShape - Shape value for Weibull distribution surfaceReflectivityLand.SpeckleScale - Scale parameter for Weibull and Rayleigh speckle distribution surfaceReflectivityLand.SpeckleShape - Shape value for Weibull distribution surfaceReflectivitySea.SpeckleScale - Scale parameter for Weibull and Rayleigh speckle distribution surfaceReflectivitySea.SpeckleShape - Shape value for Weibull distribution classreg.learning.regr.CompactRegressionTree.gather - Gather properties of Statistics and Machine Learning Toolbox object from GPU prob.NormalDistribution.cdf - Cumulative distribution function prob.NormalDistribution.icdf - Inverse cumulative distribution function prob.NormalDistribution.iqr - Interquartile range of probability distribution prob.NormalDistribution.mean - Mean of probability distribution prob.NormalDistribution.median - Median of probability distribution prob.NormalDistribution.negloglik - Negative loglikelihood of probability distribution prob.NormalDistribution.paramci - Confidence intervals for probability distribution parameters prob.NormalDistribution.pdf - Probability density function prob.NormalDistribution.plot - Plot probability distribution object prob.NormalDistribution.proflik - Profile likelihood function for probability distribution prob.NormalDistribution.random - Random numbers prob.NormalDistribution.std - Standard deviation of probability distribution prob.NormalDistribution.truncate - Truncate probability distribution object prob.NormalDistribution.var - Variance of probability distribution prob.WeibullDistribution - Weibull probability distribution object prob.WeibullDistribution.A - Scale parameter prob.WeibullDistribution.B - Shape parameter prob.WeibullDistribution.IsTruncated - Logical flag for truncated distribution prob.WeibullDistribution.NumParameters - Number of parameters prob.WeibullDistribution.ParameterCovariance - Covariance matrix of the parameter estimates prob.WeibullDistribution.ParameterIsFixed - Logical flag for fixed parameters prob.WeibullDistribution.ParameterValues - Distribution parameter values prob.WeibullDistribution.Truncation - Truncation interval prob.WeibullDistribution.DistributionName - Probability distribution name prob.WeibullDistribution.InputData - Data used for distribution fitting prob.WeibullDistribution.ParameterDescription - Distribution parameter descriptions prob.WeibullDistribution.ParameterNames - Distribution parameter names wblcdf - Weibull cumulative distribution function wblfit - Weibull parameter estimates wblinv - Weibull inverse cumulative distribution function wbllike - Weibull negative log-likelihood wblpdf - Weibull probability density function wblplot - Weibull probability plot wblrnd - Weibull random numbers wblstat - Weibull mean and variance networkTrafficVideoConference.WeibullScale - Scale parameter for Weibull distribution networkTrafficVideoConference.WeibullShape - Shape parameter for Weibull distribution
If you scan down the list of functions found, you will see wblfit. I'd bet that might help. Again, learn about the lookfor utility.
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Armel
Armel el 25 de Oct. de 2022
Thanks ! That's what I was looking for !

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