Probabilidade de Cobertura dos Intervalos de Confiança ... - Uem

36 nda = &i n d i c e ;
37 f i l e ” c : \ emv o &n&p . . dat ” mod ;
38 put nda ” ; ” parameter ” ; ” estimate ” ; ” s t a n d a r d e r r o r ;
39 run ;
40
41 data n u l l ;
42 s e t adic ( keep=l a b e l estimate s t a n d a r d e r r o r ) ;
43 nda = &i n d i c e ;
44 f i l e ” c : \ a d i c o &n&p . . dat ” mod ;
45 put nda ” ; ” l a b e l ” ; ” estimate ” ; ” s t a n d a r d e r r o r ;
46 run ;
47 %mend estimacao dados ;
48 %macro bootstrap ( inpt =, seed =, s a m p l e s i z e =, r e p l i c a c a o =,mu=, beta =, i n d i c e=
49 , n=,p=);
50 proc d a t a s e t s l i b r a r y=work ; d e l e t e sample boot emvs adic ; run ;
51
52 proc s u r v e y s e l e c t data = &inpt
53 out = sample boot ( keep=time d e l t a NumberHits r e p l i c a t e )
54 seed = &seed
55 rep = &r e p l i c a c a o
56 method= urs n = &s a m p l e s i z e noprint ;
57 run ;
58
59 proc p r i n t t o f i l e =”c : \ nda . dat ” new ;
60 run ;
61
62 proc nlmixed data=sample boot vardef=n cov tech=t r ;
63 ods output ParameterEstimates = emvs ;
64 ods output AdditionalEstimates = adic ;
65 parms mu = &mu, beta = &beta ;
66 bounds mu>0, beta >0;
67 lnh = l o g ( beta)−beta ∗ l o g (mu)+( beta −1)∗ l o g ( time ) ;
68 l n s = −(time /mu)∗∗ beta ;
69 L = numberhits ∗( d e l t a ∗ lnh+l n s ) ;
70 model L ˜ g e n e r a l (L ) ;
71 estimate ” logmediana ” l o g (mu)+(1/ beta ) ∗ ( l o g (− l o g ( 1 − 0 . 5 0 ) ) ) ;
72 estimate ”logQ1” l o g (mu)+(1/ beta )∗( l o g (− l o g ( 1 − 0 . 2 5 ) ) ) ;
73 estimate ”logQ3” l o g (mu)+(1/ beta )∗( l o g (− l o g ( 1 − 0 . 7 5 ) ) ) ;
74 by r e p l i c a t e ;
75 run ;
91