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- かずただ うばら
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1 61 SAS SAS LOHAS
2 LOHAS ( ) ( ) LOHAS 29% 35%
3 LOHAS LOHAS
4 GMO 500
5 Yes No Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22 Q23 Q24 LOHAS Q25 LOHAS /
6 2 LOHAS Q26 LOHAS Q27 Yes Yes No No LOHAS 27.64% 26.72% 27.40% LOHAS 27.97% 23.94% 27.40% χ χ p p LOHAS Yes No LOHAS 26.98% 26.28% 19.00% 21.00% 44.00% 27.40% χ p Q28 LOHAS ( ) ( ) Yes No LOHAS 27.27% 22.73% 28.57% 25.49% 40.91% 27.27% 32.05% 30.43% 27.40% χ p Q29 LOHAS 0 ~ ~ ~ ~ Yes No LOHAS 28.21% 16.67% 15.22% 27.27% 31.60% 27.40% χ p Q30 LOHAS Yes No LOHAS 19.05% 33.33% 26.67% 5.26% 17.95% 39.76% 28.57% 28.57% 28.00% 27.40% χ p Q31
7 LOHAS LOHAS LOHAS
8 LOHAS Factor Factor1 Factor2 Factor3 Factor4 Factor5 Factor Factor2 LOHAS LOHAS Factor4 Factor3 2
9 LOHAS LOHAS LOHAS LOHAS LOHAS
10 LOHAS
11 1 i I Q 1 Q 2 Q k Q K-1 Q K
12 J K I 1 i I Q 1 Q 2 Q k Q K-1 Q K M 1 j Q' 1 Q' 2 : Q' m : 11 i 1 I 1 1j ij Ij J Q' M-1 1J I 1 Q' M
13 i i Q k P ik =P(Q k =1 i) J K I 1 i I Q 1 Q 2 Q k Q K-1 Q K M 1 j Q' 1 Q' 2 : Q' m : 11 i 1 I 1 1j ij Ij J Q' M-1 1J I 1 Q' M
14 K M Q01 Q02 Q03 Q04 Q05 Q06 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q07 Q08 Q09 Q10 Q11 Q21 Q22 Q23 Q24
15 Model ik jm x nk y nm ij i kyes j myes n k Yes 1 0 n m Yes 1 0 i j L = N I J K M xnk 1 xnk θij γ ik (1 γ ik ) n= 1 i= 1 j= 1 k = 1 m= 1 δ y jm nm (1 δ jm ) 1 y nm (2)
16 Model ( Maximization) log L d = N I J n= 1 i= 1 j= 1 z nij logθ + ij N I J n= 1 i= 1 j= 1 z nij logψ K M x 1 1 nk xnk ynm ynm ψ n ij = ( γ ik )(1 γ ik ) ( δ jm )(1 δ jm) k = 1 m= 1 n ij (3) (4) Z nij n (i,j) z nij (Z Expectation) E[ z nij F] = I θ ψ ij J i= 1 j= 1 n ij θ ψ ij n ij (5)
17 Model ( Maximization) log L d = N I J n= 1 i= 1 j= 1 z nij logθ + ij M-Step N I J n= 1 i= 1 j= 1 z nij logψ K M x 1 1 nk xnk ynm ynm ψ n ij = ( γ ik )(1 γ ik ) ( δ jm )(1 δ jm) k = 1 m= 1 n ij (3) (4) Z nij n (i,j) EM z nij (Z Expectation) E[ z nij F] = I θ ψ ij J n ij θ ψ E-Step ij n ij i= 1 j= 1 (5)
18 SAS/OR NLP NLP SAS/OR
19 SAS/OR NLP /* ; /* z /* */ %macro z_generate; Z %mend z_generate; /* ; /* M_ /* */ %macro m_step; Proc NLP Data=data_set TECHNIQUE=NEWRAP outest=outest1 vardef=n cov=2 pcov pstderr; ods output "Resulting Parameters"=est_ds; run; dm "clear output"; /* output */ %mend m_step; /* ; /* E_ /* */ %macro e_step; z z %mend e_step; /* ; /* /* */ %Macro Main; /* z */ %z_generate; %Mend; %Main; /* */ %do a=1 %To &xa; %m_step; %e_step; /* z goto */ %if &STOPFLAG=1 %then %do;%goto FINISH;%end; %end; %FINISH:
20 AIC AIC K (i ) M (j ) AIC AIC
21 θ θ θ θ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ δ δ δ δ δ δ δ δ δ δ δ δ δ δ δ δ δ δ
22 θ θ θ θ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ γ δ δ δ δ δ δ δ δ δ δ δ δ δ δ δ δ δ δ
23 K M j=1 j=2 i= i=
24 Conclusion
25 URL
26
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27 3 27 ) Ising Landau Synergetics Fokker-Planck F-P Landau F-P Gizburg-Landau G-L G-L Bénard/ Hopfield H.Haken Synergetics 2nd (1978) (1) Ising m T T C 1: m h Hamiltonian H = J ij S i S j h i S
2 G(k) e ikx = (ik) n x n n! n=0 (k ) ( ) X n = ( i) n n k n G(k) k=0 F (k) ln G(k) = ln e ikx n κ n F (k) = F (k) (ik) n n= n! κ n κ n = ( i) n n k n
. X {x, x 2, x 3,... x n } X X {, 2, 3, 4, 5, 6} X x i P i. 0 P i 2. n P i = 3. P (i ω) = i ω P i P 3 {x, x 2, x 3,... x n } ω P i = 6 X f(x) f(x) X n n f(x i )P i n x n i P i X n 2 G(k) e ikx = (ik) n
Autumn 2007 1 5 8 12 14 14 15 %!SASROOT/sassetup SAS Installation Setup Welcome to SAS Setup, the program used to install and maintain your SAS software. SAS Setup guides you through a series of menus