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SAS die-hard

Find out what else SAS can do. Tuesday, April 17, 2012. Parameter estimation for univariate beta distribution. 1 Generate random sample respectively from Beta1, 1, Beta1, 2, Beta1, 3, Beta2, 1, Beta2, 2, Beta2, 3, Beta3, 1, Beta3, 2, Beta3, 3, each with sample size 200;. 2 Compute sample mean and sample variance, and based on them then compute moments estimators of alpha and beta;. Alpha, beta;. ParameterEstimates MLE Est;. Using MM estimates as starting points. Links to this post.

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SAS die-hard

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Find out what else SAS can do. Tuesday, April 17, 2012. Parameter estimation for univariate beta distribution. 1 Generate random sample respectively from Beta1, 1, Beta1, 2, Beta1, 3, Beta2, 1, Beta2, 2, Beta2, 3, Beta3, 1, Beta3, 2, Beta3, 3, each with sample size 200;. 2 Compute sample mean and sample variance, and based on them then compute moments estimators of alpha and beta;. Alpha, beta;. ParameterEstimates MLE Est;. Using MM estimates as starting points. Links to this post.

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This web page sasdiehard.blogspot.com states the following, "Find out what else SAS can do." We saw that the webpage said " Tuesday, April 17, 2012." It also said " Parameter estimation for univariate beta distribution. 1 Generate random sample respectively from Beta1, 1, Beta1, 2, Beta1, 3, Beta2, 1, Beta2, 2, Beta2, 3, Beta3, 1, Beta3, 2, Beta3, 3, each with sample size 200;. 2 Compute sample mean and sample variance, and based on them then compute moments estimators of alpha and beta;. ParameterEstimates MLE Est;. Using MM estimates as starting points."

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