Posts Tagged ‘ PROC GLIMMIX ’

Benchmark Regression Procedures using OLS Regression

August 18, 2011
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Rick Wicklin discussed in his blog the performance in solving a linear system using SOLVE() function and INV() function from IML. Since regression analysis is an integral part of SAS applications and there are many SAS procedures in SAS/STAT that a...
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Benchmark Regression Procedures using OLS Regression

August 18, 2011
By

Rick Wicklin discussed in his blog the performance in solving a linear system using SOLVE() function and INV() function from IML. Since regression analysis is an integral part of SAS applications and there are many SAS procedures in SAS/STAT that a...
Read more »

Tags: , , , , ,
Posted in SAS | Comments Off

Benchmark Regression Procedures using OLS Regression

August 18, 2011
By

Rick Wicklin discussed in his blog the performance in solving a linear system using SOLVE() function and INV() function from IML. Since regression analysis is an integral part of SAS applications and there are many SAS procedures in SAS/STAT that a...
Read more »

Tags: , , , , ,
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%HPGLIMMIX macro on large scale HMM

June 7, 2011
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PROC GLIMMIX is good tool for generalized linear mixed model (GLMM), when the scale is small to medium. When facing a large scale GLMM, such as modeling all ZIPs nested in Counties nested in all 51 States in US, a 64-bit machine with extremely large ...
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%HPGLIMMIX macro on large scale HMM

June 7, 2011
By

PROC GLIMMIX is good tool for generalized linear mixed model (GLMM), when the scale is small to medium. When facing a large scale GLMM, such as modeling all ZIPs nested in Counties nested in all 51 States in US, a 64-bit machine with extremely large ...
Read more »

Tags: , , ,
Posted in SAS | Comments Off

%HPGLIMMIX macro on large scale HMM

June 7, 2011
By

PROC GLIMMIX is good tool for generalized linear mixed model (GLMM), when the scale is small to medium. When facing a large scale GLMM, such as modeling all ZIPs nested in Counties nested in all 51 States in US, a 64-bit machine with extremely large ...
Read more »

Tags: , , ,
Posted in SAS | Comments Off

Low Rank Radial Smoothing using GLIMMIX and its Scoring

September 30, 2010
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Low Rank Radial Smoothing using GLIMMIX , a semiparametric approach to smooth curves . Specifying TYPE=RSMOOTH option in RANDOM statement, we can implement this spline smooth approach. The bast thing is that for future scoring, data preparation...
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