| 期刊全稱 | A SAS/IML Companion for Linear Models | | 影響因子2023 | Jamis J. Perrett | | 視頻video | http://file.papertrans.cn/143/142092/142092.mp4 | | 發(fā)行地址 | Includes supplementary material: | | 學(xué)科分類 | Statistics and Computing | | 圖書封面 |  | | 影響因子 | .Linear models courses are often presented as either theoretical or applied. Consequently, students may find themselves either proving theorems or using high-level procedures like PROC GLM to analyze data. There exists a gap between the derivation of formulas and analyses that hide these formulas behind attractive user interfaces. This book bridges that gap, demonstrating theory put into practice...Concepts presented in a theoretical linear models course are often trivialized in applied linear models courses by the facility of high-level SAS procedures like PROC MIXED and PROC REG that require the user to provide a few options and statements and in return produce vast amounts of output. This book uses PROC IML to show how analytic linear models formulas can be typed directly into PROC IML, as they were presented in the linear models course, and solved using data. This helps students see the link between theory and application. This also assists researchers in developing new methodologies in the area of linear models...The book contains complete examples of SAS code for many of the computations relevant to a linear models course. However, the SAS code in these examples automates the | | Pindex | Textbook 2010 |
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