sasdiehard.blogspot.com

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 Beta(1, 1), Beta(1, 2), Beta(1, 3), Beta(2, 1), Beta(2, 2), Beta(2, 3), Beta(3, 1), Beta(3, 2), Beta(3, 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 | sasdiehard.blogspot.com Reviews

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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 Beta(1, 1), Beta(1, 2), Beta(1, 3), Beta(2, 1), Beta(2, 2), Beta(2, 3), Beta(3, 1), Beta(3, 2), Beta(3, 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 | sasdiehard.blogspot.com Reviews

https://sasdiehard.blogspot.com

Find out what else SAS can do. Tuesday, April 17, 2012. Parameter estimation for univariate beta distribution. 1 Generate random sample respectively from Beta(1, 1), Beta(1, 2), Beta(1, 3), Beta(2, 1), Beta(2, 2), Beta(2, 3), Beta(3, 1), Beta(3, 2), Beta(3, 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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sasdiehard.blogspot.com

1

SAS die-hard: February 2011

http://sasdiehard.blogspot.com/2011_02_01_archive.html

Find out what else SAS can do. Friday, February 18, 2011. Delete consecutive rows that match a pattern. This is a question from statistics@mitbbs.com : how to delete consecutive rows that match a pattern. Supposed we have a data set like:. And we would like to delete all consecutive rows with the pattern like:. It seems to be a simple problem in other language by using linked list or pointer or stack or anything else, but in SAS. :(. Read the dataset row by row. The codes are as following:. Drop n match;.

2

SAS die-hard: March 2011

http://sasdiehard.blogspot.com/2011_03_01_archive.html

Find out what else SAS can do. Wednesday, March 16, 2011. Fitting Logistic Regression in DATA STEP (1)- stochastic gradient descent. A brief review of gradient descent algorithms can be found on wiki http:/ en.wikipedia.org/wiki/Gradient descent. As well as the entry about stochastic gradient descent http:/ en.wikipedia.org/wiki/Stochastic gradient descent. The dataset used as example is from UCLA stat computing http:/ www.ats.ucla.edu/stat/data/hsb2.sas7bdat. Variables of students’ scores on read,...

3

SAS die-hard: July 2011

http://sasdiehard.blogspot.com/2011_07_01_archive.html

Find out what else SAS can do. Thursday, July 21, 2011. Randomly divide data into N groups. The following codes show a fast way of random division on a dataset. Do id= 1 to 547;. Length UnFilledGrpIdx $ 100 ;. Set test nobs= nobs;. Array Quota{&Grp.} temporary (&Grp.*0);. Retain UnFilledGrpIdx " " UnFilledGrpCnt &Grp. If N =1 then do;. Do i=1 to &Grp;. Quota[ i]=round( nobs/(&Grp.- i 1) ;. Nobs= nobs- Quota[ i];. UnFilledGrpIdx=cats( UnFilledGrpIdx, put( i, 3.0), " " );. Quota[ GrpID]= Quota[ GrpID]-1;.

4

SAS die-hard: Randomly divide data into N groups

http://sasdiehard.blogspot.com/2011/07/randomly-divide-data-into-n-groups.html

Find out what else SAS can do. Thursday, July 21, 2011. Randomly divide data into N groups. The following codes show a fast way of random division on a dataset. Do id= 1 to 547;. Length UnFilledGrpIdx $ 100 ;. Set test nobs= nobs;. Array Quota{&Grp.} temporary (&Grp.*0);. Retain UnFilledGrpIdx " " UnFilledGrpCnt &Grp. If N =1 then do;. Do i=1 to &Grp;. Quota[ i]=round( nobs/(&Grp.- i 1) ;. Nobs= nobs- Quota[ i];. UnFilledGrpIdx=cats( UnFilledGrpIdx, put( i, 3.0), " " );. Quota[ GrpID]= Quota[ GrpID]-1;.

5

SAS die-hard: Please converge, PROC NLMIXED....

http://sasdiehard.blogspot.com/2011/11/please-converge-proc-nlmixed.html

Find out what else SAS can do. Wednesday, November 9, 2011. Please converge, PROC NLMIXED. Proc NLMIXED is very powerful since I love its flexibility for self-defined likelihood function and various optimization options. Unfortunately convergence problem is always a pain in the neck. To illustrate this, let me use an example from SAS/STAT user guide. The example data and codes can be found here:. Sample code is straight forward:. However, what if you don't know the right starting values for parameters?

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sasdiehard.blogspot.com

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 Beta(1, 1), Beta(1, 2), Beta(1, 3), Beta(2, 1), Beta(2, 2), Beta(2, 3), Beta(3, 1), Beta(3, 2), Beta(3, 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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