多元统计分析方法练习题(10)

6 0 1 16 1 1 32 0 1 2 1 2 8 1 2 15 1 2 7 1 1 17 0 1 32 0 1 3 1 2 8 1 2 17 1 2 9 0 1 19 0 1 34 0 1 4 1 2 8 1 2 22 1 2 10 1 1 20 0 1 35 0 1 4 1 2 1 1 2 23 1 2 ;

PROC LIFEREG OUTEST =MODELS COVOUT; A：MODEL stime * out(0)=g;

B:MODEL stime * out(0)=g/DIST=EXPONENTIAL; C:MODEL stime * out(0)=G/DIST=WEIBULL; RUN; 练习8.4 DATA ex8 _4; INPUT time @@ ; G=1; OUT=1;

CARDS;

1 2 3 4 5 5 9 13 16. 5 17. 5 12. 5 7 6 17. 5 6 14 25 49 37. 5 49 28 PROC LIFEREG OUTEST=MODELS COVOUT; A :MODEL time=g/DIST=WEIBULL; B:MODEL time=g /DIST=EXPONENTIAL ; RUN;

PROC PRINT DATA=MODELS ; ID _MODEL -; RUN;

练习 8. 5 DATA ex8 _5;

INPUT id group stime censor kidney @@; CARDS;

1 0 8 1 1 2 0 852 0 0 ... ... ...

25 1 1990 0 0

/ *指数回归和 Weibull回归 * /

PROC LIFEREG OUTEST=MODELS COVOUT;

A : MODEL stime * censor (0) = group kidney /DIST = WEIBULL ;

B : MODEL stime * censor ( O) = group kidney /DIST = EXPONENTIAL ; RUN;

PROC PRINT DATA=MODELS ; ID _MODEI_ _; RUN;

/ * Cox比例风险 * / PROC PHREG ;

MODEL stime * censor (O) = group kidney ; RUN;

练习 8. 6 DATA ex8 _6;

INPUT id censor stime agel bmi ageo smk sbp dbp ecg chd; mbp=sbp/3+2 * dbp/3; CARDS ;

1 0 12. 4 44 34. 2 41 0 132 96 0 ... ... ...

149 0 10. 5 49 30. 8 47 1 146 86 0 PROC PHREG; .

MODEL stime * censor (0) = agel mbp ecg/SELECTION = STEPWISE SLENTRY = 0. 2 SLSTAY = 0. I ; RUN;

综习 8. 7

OPTION ls=100; DATA ex8 _7;

INPUT age gender to YYMMDDIO. response tl YYMMDDlO. outcome ii bl 12 b2 13 b3 14 b4 is b5;

sl=ii * bl; s2=12 * b2; s3=13 * b3;s4=14 * b4; s5=is * b5; time=tl-t0; CARDS;

0 0 53 0 1977/3/31 1 1977/11/1 0 7 7 23 23 0 0 25 25 0 0 ... ... ...

59 1 1977/3/4 0 1977/4/2 1 0 0 0 0 0 0 16 16 0 0 ； run；

proc phreg；

model time * outcome(0)=age gender response s1 s2 s3 s4 s5; run;

?1??1??0????10.9???1??0??答案：9-1点A到均数的距离为：?????????????????1.0526316

100.91???1??0??????????1??1??0????10.9???1??0?? 点B到均数的距离为：?????????????????20

???1??0???0.91????1??0??答案：9-2 DATA ex9-2;

INPUT item $ y1 y2; CARDS;

X1 27.892 61.42 ……

X13 20.913 61.25 ;

PROC STANDARD MEAN=0 STD=1 OUT=temp; VAR y1 y2;

/* 最长距离法 */

PROC CLUSTER DATA=temp METHOD=SINGLE STD NOSQUARE CCC; VAR y1 y2; ID item; RUN;

PROC TREE HORIZONTAL SPACE=3; ID item; RUN;

/* 最长距离法 */

PROC CLUSTER DATA=temp METHOD=COMPLETE STD NOSQUARE CCC; VAR y1 y2; ID item; RUN;

PROC TREE HORIZONTAL SPACE=3; ID item; RUN;

/* 类平均法*/

PROC CLUSTER DATA=temp METHOD=average STD NOSQUARE CCC; VAR y1 y2; ID item; RUN;

PROC TREE HORIZONTAL SPACE=3; ID item; RUN;

/*重心法*/

PROC CLUSTER DATA=temp METHOD=centroid STD NOSQUARE CCC; VAR y1 y2; ID item; RUN;

PROC TREE HORIZONTAL SPACE=3; ID item; RUN;

X1 X2 X4 X7 X8 X13 X9 X12 X3 X5 X6 X11 X10

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Minimum Distance Between Clusters x1 x2 x3 x5 x6

x4 x8 x7 x13 x9 x12 x11 x10

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 Maximum Distance Between Clusters X1 X2 X4 X7 X8 X13 X9 X12 X11 X3 X5 X6 X10

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Average Distance Between Clusters X1 X2 X4 X7 X8 X13 X9 X12 X11 X3

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