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1 For Higher Customer Satisfaction, We Bridge the SAS System Between Customer s World. TheSign that Leads to the Goalfor Sure

2 02 lp plp p p pp x=lpnorm(1.5,1,-4); /*x=(1**1.5+4**1.5)**(1/1.5)=4.3267*/ y=sumabs(3,-2,5); /*y=3+2+5=10*/ z=euclid(4,-2,3,1); /*z=sqrt(4**2+2**2+3**2+1**2)=5.4772*/ l p l_infinity_norm1=lpnorm( ,of x1-x10); l_infinity_norm2=max(of x1-x10)<>-min(of x1-x10); x=gcd(12,48,16); y=lcm(4,6,18); /*1*/ /*2*/ /*x=4*/ /*y=36*/

$03 DATA knots; INPUT x y; DATALINES; 1.0 2.0 2.5 3.0 2.5 4.0 3.0 4.5 7.0 6.0 8.0 4.0 9.0 4.5 ; DATA plots; ARRAY _x{7}; ARRAY _y{7}; DO i=1 TO 7; SET knots; _x{i}=x; _y{i}=y; OUTPUT; y=.$

3 03 DATA knots; INPUT x y; DATALINES; ; DATA plots; ARRAY _x{7}; ARRAY _y{7}; DO i=1 TO 7; SET knots; _x{i}=x; _y{i}=y; OUTPUT; y=.; DO x=0 TO 10 BY 0.01; y2=msplint(x,7,of _x{*},of _y{*}); OUTPUT; DROP _x: _y: i; PROC SGPLOT DATA=plots NOAUTOLEG SCATTER Y=y X=x / MARKERATTRS=(SYMBOL=CIRCLEFILLED SIZE=8PT); SERIES Y=y2 X=x / LINEATTRS=(PATTERN=1); DATA _NULL_; ARRAY x[3]; k=-1; DO i=1 TO 2**DIM(x); rc=graycode(k, OF x[*]); PUT i x[*] rc=; rc= rc= rc= rc= rc= rc= rc= rc=1 BLACKCLPRC BLACKPTPRC BLKSHCLPRC BLKSHPTPRC GARKHCLPRC GARKHPTPRC MARGRCLPRC MARGRPTPRC

4 04 DATA _NULL_; INFORMAT d1-d5 NLDATE14.; INPUT v1 d1 v2 d2 v3 d3 v4 d4 v5 d5 r = FINANCE('XIRR', of v1-v5, of d1-d5, 0.1); PUT r=; DATALINES; ; r= DATA _NULL_; ARRAY x[5] $6 (); n=5;k=2; /**/ DO j=1 TO COMB(n,k)+1; rc=allcomb(j, k, OF x[*]); /*ALLCOMB*/ PUT j= rc= x1= x2=; j=1 rc=0 x1= x2= j=2 rc=2 x1= x2= j=3 rc=2 x1= x2= j=9 rc=2 x1= x2= j=10 rc=1 x1= x2= j=11 rc=-1 x1= x2= DATA _NULL_; ARRAY x[5] $6 (); n=5;k=3; /**/ DO UNTIL(rc<0); j+1; rc=lexcomb(j, k, of x[*]); /*LEXCOMB*/ PUT rc= j= x1= x2= x3=; rc=1 j=1 x1= x2= x3= rc=3 j=2 x1= x2= x3= rc=2 j=3 x1= x2= x3= rc=2 j=4 x1= x2= x3= rc=1 j=5 x1= x2= x3= rc=-1 j=6 x1= x2= x3= PROC FCMP OUTLIB=SASUSER.myfunc.test1; FUNCTION boxcox(x,lambda); IF x>0 THEN DO; IF ABS (lambda)>1e-4 THEN f=(x**lambda-1)/lambda; ELSE f=log (x); ELSE f=.; RETURN (f); ENDSUB;

5 05 OPTIONS CMPLIB=SASUSER.myfunc; DATA _null_; y=boxcox(3,-2); PUT y=; PROC FCMP OUTLIB=SASUSER.mysub.a; SUBROUTINE swap(a,b); OUTARGS a,b; _temp=b; b=a; a=_temp; ENDSUB; /*y= */ OPTIONS CMPLIB=SASUSER.mysub; DATA _null_; x=3;y=2; /*x=3 y=2*/ CALL swap(x, y); /*swap*/ PUT x= y=; /*x=2 y=3*/ PROC FCMP OUTLIB=SASUSER.myfunc.recursion; FUNCTION factorial(n); IF n<0 or INT(n) NE n THEN f=.; ELSE IF n=0 THEN f=1; ELSE f=factorial(n-1)*n; factorial*/ RETURN (f); ENDSUB; OPTIONS CMPLIB=SASUSER.myfunc; DATA _null_; x=factorial(4); PUT x=; /*4!*/ /*x=24*/ PROC FCMP; FUNCTION equation3(a,b,c,d,x); f=a*x**3+b*x**2+c*x+d; RETURN (f); ENDSUB; y=0; x = SOLVE("equation3",{.},y,1,3,4,2,.); PUT x=; /*x=-1*/

06 ODS HTML CLOSE; ODS GRAPHICS ON / IMAGEMAP; ODS

23 26 43 32 54 30 40 23 32 38 30 24 38 ; PROC FORMAT;

6 06 ODS HTML CLOSE; ODS GRAPHICS ON / IMAGEMAP; ODS HTML; PROC CORR DATA=sashelp.class PLOTS=(MATRIX); ID name sex; VAR height weight age; DATA class; INPUT gender$ DATALINES; ; PROC FORMAT; PICTURE pctfmt (ROUND) OTHER='009.9%'; VALUE agefmt LOW-29='30' 30-39="30" 40-HIGH="40";

7 07 PROC TEMPLATE; DEFINE CROSSTABS Base.Freq.CrossTabFreqs; DEFINE HEADER tabletitle; TEXT ":" _ROW_NAME_ " :" _COL_NAME_; CELLVALUE Frequency Percent Rowpercent; DEFINE Frequency; FORMAT=8.; HEADER=''; DEFINE Percent; FORMAT=pctfmt.; HEADER=''; DEFINE Rowpercent; FORMAT=pctfmt.; HEADER=''; HEADER tabletitle; PROC FREQ DATA=CLASS; TABLES gender*age; FORMAT age agefmt.; :gender :age % 14.3% 21.4% 57.1% 37.5% 25.0% 37.5% % 28.6% 0.0% 42.9% 33.3% 66.7% 0.0% % 42.9% 21.4% 100.0% DATA data2; INPUT group x$ resp freq; DATALINES; 1 A A B B A A B B 0 22 ; ODS GRAPHICS ON; PROC FREQ DATA=data2 ORDER=DATA; TABLES group*x*resp/relrisk PLOTS=(ODDSRATIOPLOT); WEIGHT freq; TABLES drug*respnse / RISKDIFF(NONINF MARGIN=0.1);

8 08 DATA data3; INPUT x DATALINES; ; PROC FREQ DATA=data3; TABLES x / BINOMIAL(LEVEL="1" WILSON AGRESTICOULL); WEIGHT freq; x = % Wilson Agresti-Coull DATA data4; INPUT drug$ resp freq; DATALINES; A 1 6 A 0 9 B 1 4 B 0 11 ; PROC FREQ DATA=data4 ORDER=DATA; TABLES drug*resp / RISKDIFF; WEIGHT freq; EXACT RISKDIFF; 1 ) 95% () DATA data5; INPUT DATALINES; ; PROC RANK DATA=data5 OUT=out5 TIES=DENSE; /*TIES=DENSE*/ VAR value; RANKS denserank; PROC PRINT DATA=out5; OBS value denserank

09 DATA data6; CALL STREAMINIT(12345); DO group=1 to 3; DO i=1 TO 20; x=rand('normal',group,2); OUTPUT; DROP i; ODS GRAPHICS ON; PROC UNIVARIATE DATA=data6; CLASS group; CDFPLOT x /NORMAL OVERLAY;

9 09 DATA data6; CALL STREAMINIT(12345); DO group=1 to 3; DO i=1 TO 20; x=rand('normal',group,2); OUTPUT; DROP i; ODS GRAPHICS ON; PROC UNIVARIATE DATA=data6; CLASS group; CDFPLOT x /NORMAL OVERLAY; PROC UNIVARIATE DATA=SASHELP.CLASS OUTTABLE=out7; VAR _NUMERIC_; PROC PRINT DATA=out7 LABEL; Variable Variable Standard Name Label Mean Deviation Variance Age Height Weight st Skewness Kurtosis Minimum Percentile ()

10 10 SAS Academic News

11 11

12 12 r x i x y i y (x i - x) (y i - y) (x i - x) (y i - y) 2 2 xx yy

13 13 proc gplot data=data1; /**/ plot y*x; run; /**/ proc corr data=data1 outp=wk1 outs=wk2 pearson spearman; /*?*/ var x y; run;

14 14

15 Q&A Q A DAT sample; SET sashelp.clas; %PUT &SYSWARNINGTEXT; %PUT &SYSERRORTEXT; 1 DAT sample; --- 14 WARNING 14-169: DAT DATA 2 SET sashelp.clas; ERROR: SASHELP.CLAS.DATA 3 NOTE: WARNING: WORK.

15 15 Q&A Q A DAT sample; SET sashelp.clas; %PUT &SYSWARNINGTEXT; %PUT &SYSERRORTEXT; 1 DAT sample; WARNING : DAT DATA 2 SET sashelp.clas; ERROR: SASHELP.CLAS.DATA 3 NOTE: WARNING: WORK.SAMPLE 0 0 NOTE: DATA 0.06 CPU %PUT "&SYSWARNINGTEXT"; " WORK.SAMPLE %PUT "&SYSERRORTEXT"; " SASHELP.CLAS.DATA Q A!DI Studio etlstudio.ini CommandLineArgs=-Xmx1024m -Djava.system.class.loader =com.sas.app... CommandLineArgs=-Xmx1024m -Xss512k -Djava.system. class.loader=com... Q A LIBNAME mylib"c: temp mylib"; /* */ DATA mylib.class work.class; SET sashelp.class; DATA mylib.prdsale work.prdsale; SET sashelp.prdsale;

16 16 DATA _NULL_; /* */ SET sashelp.vmember(keep=memname libname memtype WHERE=(LIBNAME=UPCASE("mylib") AND MEMTYPE="DATA")); /* COMPARE */ CALL EXECUTE("PROC COMPARE BASE=mylib." memname); CALL EXECUTE(" COMPARE=work." memname); CALL EXECUTE(";"); CALL EXECUTE(""); Q A 5 NOTE: WORK.IN 1 1 NOTE: DATA (): 0.01 CPU /* */ 7 DATA out; 8 SET in(drop=b); 9 NOTE: WORK.IN 1 NOTE: WORK.OUT 1 1 NOTE: DATA (): 0.00 CPU OPTIONS DKROCONDNOWARN; 12 /* */ 13 DATA test; 14 A=123; 15 DROP b; 16 NOTE: WORK.TEST 1 1 NOTE: DATA (): 0.00 CPU 0.00 OPTIONS DKRICONDNOWARN; DATA in; A=123; DATA out; SET in(drop=b); OPTIONS DKROCONDNOWARN; DATA test; A=123; DROP b; /* */ /* */ /* */ 1 OPTIONS DKRICONDNOWARN; 2/* */ 3 DATA in; 4 A=123; Q A /* */ DATA test; INPUT Id1 id2 ID3 amount1 Amount2 amount3 Sales1 sales2 Sales3 returns1 Returns2 returns3 x1 x2 X10; CARDS; ; /* ORDERIGNORECASE */ PROC CONTENTS DATA=work.test ORDER=IGNORECASE;

17 17 # 4 amount1 8 5 Amount2 8 6 amount3 8 1 Id1 8 2 id2 8 3 ID returns Returns returns3 8 7 Sales1 8 8 sales2 8 9 Sales x x X ID returns Returns returns3 8 7 Sales1 8 8 sales2 8 9 Sales x X x2 8 Q A # 5 Amount2 8 3 ID3 8 1 Id Returns2 8 7 Sales1 8 9 Sales X amount3 8 4 amount1 8 2 id returns returns3 8 8 sales x x2 8 # 1 amount1 8 5 Amount2 8 6 amount3 8 1 Id1 8 2 id2 8 Q A PROC GLIMMIX DATA=one ODDSRATIO; CLASS treat gender; MODEL resp = treat gender / DIST=BINOMIAL LINK=LOGIT;

18 18 SAS Training

19 19

20 20 Latest Releases SAS Institute Japan

プリント

プリント For Higher Customer Satisfaction, We Bridge the SAS System Between Customer s World. YourModelsBuild up Your NextAnalytics 02 Y β0 β1x1 β2x2 ε Y ~ μ σ 2 μ β0 β1x1 β2x2 Y ~ n p logit(p) β0 β1x1 β2x2 logit(p)logit(p)=log(p/(1-p))