Download A SAS/IML companion for linear models by Jamis J. Perrett PDF

By Jamis J. Perrett

Linear versions classes are frequently provided as both theoretical or utilized. accordingly, scholars may possibly locate themselves both proving theorems or utilizing high-level approaches like PROC GLM to research info. There exists a spot among the derivation of formulation and analyses that cover those formulation in the back of beautiful consumer interfaces. This publication bridges that hole, demonstrating concept positioned into perform.

Concepts awarded in a theoretical linear versions path are frequently trivialized in utilized linear types classes by way of the ability of high-level SAS methods like PROC combined and PROC REG that require the person to supply a number of ideas and statements and in go back produce substantial quantities of output. This publication makes use of PROC IML to teach how analytic linear types formulation might be typed at once into PROC IML, as they have been offered within the linear versions direction, and solved utilizing info. This is helping scholars see the hyperlink among conception and alertness. This additionally assists researchers in constructing new methodologies within the sector of linear types.

The booklet includes entire examples of SAS code for plenty of of the computations suitable to a linear versions path. besides the fact that, the SAS code in those examples automates the analytic formulation. The code for high-level systems like PROC combined is additionally incorporated for side-by-side comparability. The e-book computes uncomplicated descriptive records, matrix algebra, matrix decomposition, probability maximization, non-linear optimization, and so on. in a structure conducive to a linear versions or a different subject matters direction.

Also incorporated within the booklet is an instance of a easy research of a linear combined version utilizing constrained greatest chance estimation (REML). the instance demonstrates exams for fastened results, estimates of linear services, and contrasts. the instance begins by means of exhibiting the stairs for interpreting the knowledge utilizing PROC IML after which offers the research utilizing PROC combined. this enables scholars to stick with the method that result in the output.

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Extra info for A SAS/IML companion for linear models

Example text

TXT using column input. Second, the column vectors STUDENTS and HEIGHTS are created from the SAS data set CLASS_D within PROC IML. This two-step approach, the data step and then the PROC IML step, is employed as column input is not directly supported in PROC IML. In the INPUT statement the starting and ending locations of the two columns are specified. The text file column containing the student data values begins at location 1 and ends at location 14. The dollar sign ($) specifies the STUDENT variable as character.

RUN; PROC PRINT DATA=info; RUN; PROC IML; dep_table = {15 17 20 25 30 STORE dep_table; SHOW STORAGE; QUIT; 13 14 17 20 25 10 8 6 11 7 5 13 11 10 15 12 8 20 15 10 3 3 6 5 5 1 1 4 3 1 1 1 1 1 1 1, 1, 1, 1, 1}; PROC IML; LOAD dep_table; USE info; READ ALL VAR{type,age} INTO info2; EDIT info; DO i=1 TO NROW(info2); value = dep_table[info2[i],info2[i,2]]; REPLACE POINT i; END; CLOSE info; QUIT; PROC PRINT DATA = info; RUN; The DATA step creates the SAS data set INFO with values for the variables ID, TYPE, and AGE.

Additionally, there may be raw data with a format that is not recognized by one of the specific informats currently supported by SAS. In that case, data may have to be read in as text and then converted, say, within a DATA step. For example, if a Social Security number would be read in as plain text. There is no special informat for identifying a Social Security number as it is read into SAS from an external text file. Though, after being read into SAS the text could then be manipulated in a DATA step if one wished to conduct an analysis involving the digits.

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