SET NOECHO
PROC OLS
* THIS PROC WILL PRODUCE THE SAME OUTPUT AS THE SHAZAM OLS COMMAND
SET NODOECHO
COPY [DEPVAR] Y_
* DEFINE THE VECTOR OF ONES AS BELOW TO GET THE DIMENSIONS RIGHT
MATRIX ONE_=Y_-Y_+1
GEN1 N_=$ROWS
COPY [INDEPS] ONE_ X_
SAMPLE 1 N_
MATRIX B_=INV(X_'X_)*X_'Y_
GEN1 K_=$ROWS
MATRIX YHAT_=X_*B_
MATRIX E_=Y_-YHAT_
MATRIX SSE_=E_'E_
GEN1 DF_=N_-K_
MATRIX SIG2_=SSE_/DF_
* COMPUTE Y'Y IN DEVIATIONS FROM MEAN, THIS REQUIRES THE A MATRIX, THEIL 4.2
MATRIX A_=IDEN(N_)-(1/N_)*(ONE_*ONE_')
* DO ANOVA STUFF FROM MEAN
MATRIX SST_=Y_'A_*Y_
MATRIX SSR_=SST_-SSE_
MATRIX R2_=1-SSE_/SST_
MATRIX KM1_=K_-1
MATRIX NM1_=N_-1
MATRIX R2ADJ_=1-(NM1_/DF_)*(1-R2_)
MAT SIGMA_=SQRT(SIG2_)
MAT YMEAN_=Y_'ONE_/N_
MATRIX MST_=SST_/NM1_
MAT SIGML_=SSE_/N_
MAT LLF_=-(N_/2)*LOG(2*3.14159*SIGML_)-(N_/2)
PRINT N_ R2_ R2ADJ_ SIG2_ SIGMA_ SSE_ YMEAN_ LLF_
* DO THE MODEL SELECTION TESTS
GEN1 FPE_=SIG2_*(1+K_/N_)
GEN1 LOGAIC_=LOG(SIGML_)+2*K_/N_
GEN1 LOGSC_=LOG(SIGML_)+K_*LOG(N_)/N_
GEN1 GCV_=SIGML_*(1-K_/N_)**(-2)
GEN1 HQ_=SIGML_*LOG(N_)**(2*K_/N_)
GEN1 RICE_=SIGML_/(1-2*K_/N_)
GEN1 SHIBATA_=SIGML_*(N_+2*K_)/N_
GEN1 SC_=SIGML_*N_**(K_/N_)
GEN1 AIC_=SIGML_*EXP(2*K_/N_)
PRINT FPE_ LOGAIC_ LOGSC_ GCV_ HQ_ RICE_ SHIBATA_ SC_ AIC_
MATRIX MSR_=SSR_/KM1_
MATRIX F_=MSR_/SIG2_
*PRINT SSR_ SSE_ SST_ KM1_ DF_ NM1_ MSR_ SIG2_ MST_ F_
* MAKE AN ANOVA TABLE
DIM ANOVA_ 3 4
MATRIX ANOVA_(1,1)=SSR_
MATRIX ANOVA_(2,1)=SSE_
MATRIX ANOVA_(3,1)=SST_
MAT ANOVA_(1,2)=KM1_
MAT ANOVA_(2,2)=DF_
MAT ANOVA_(3,2)=NM1_
MAT ANOVA_(1,3)=MSR_
MAT ANOVA_(2,3)=SIG2_
MAT ANOVA_(3,3)=MST_
MAT ANOVA_(1,4)=F_
PRINT ANOVA_
* DO ANOVA STUFF FROM ZERO
MATRIX ZSST_=Y_'Y_
MATRIX ZSSR_=ZSST_-SSE_
MATRIX ZMSR_=ZSSR_/K_
MATRIX ZMST_=ZSST_/N_
MATRIX ZF_=ZMSR_/SIG2_
* MAKE A ZANOVA TABLE
DIM ZANOVA_ 3 4
MATRIX ZANOVA_(1,1)=ZSSR_
MATRIX ZANOVA_(2,1)=SSE_
MATRIX ZANOVA_(3,1)=ZSST_
MAT ZANOVA_(1,2)=K_
MAT ZANOVA_(2,2)=DF_
MAT ZANOVA_(3,2)=N_
MAT ZANOVA_(1,3)=ZMSR_
MAT ZANOVA_(2,3)=SIG2_
MAT ZANOVA_(3,3)=ZMST_
MAT ZANOVA_(1,4)=ZF_
*PRINT ZSSR_ SSE_ ZSST_ K_ DF_ N_ ZMSR_ SIG2_ ZMST_ ZF_
PRINT ZANOVA_
* PRINT COEFFICENT TABLE
MATRIX VB_=SIG2_*INV(X_'X_)
MATRIX SE_=SQRT(DIAG(VB_))
MATRIX T_=B_/SE_
MATRIX PARTIAL_=T_/SQRT(T_**2+DF_)
?STAT X_ / MEAN=XBAR_ STDEV=SD_
MATRIX STANDB_=B_*SD_/SQRT(MST_)
MATRIX ELAS_=B_*XBAR_/YMEAN_
PRINT B_ SE_ T_ PARTIAL_ STANDB_ ELAS_ VB_
* RESIDUALS
*PRINT Y_ YHAT_ E_
* DURBIN-WATSON
* NEED TO GENERATE THE DW A MATRIX AS SHOW IN THE SHAZAM MANUAL
* PROGRAMMING EXAMPLE FOR THE EXACT DW TEST
GENR D_=2
SAMPLE 1 1
GENR D_=1
SAMPLE N_ N_
GENR D_=1
SAMPLE 1 N_
MATRIX A_=IDEN(N_,2)
MATRIX A_=-(A_+A_')+DIAG(D_)
MATRIX DW_=(E_'A_*E_)/SSE_
MATRIX VN_=DW_*(N_/NM1_)
* NOW WE NEED AN A MATRIX THAT WILL GENERATE RHO
?DELETE A_
MAT A_=IDEN(N_,2)
MAT RHO_=(E_'A_*E_)/(SSE_ - ((E_(N_))**2) )
MAT ESUM_=E_'ONE_
MAT EABS_=ABS(E_)'ONE_
* NEED THE DEVIATION A MATRIX AGAIN FOR Y AND YHAT
MATRIX A_=IDEN(N_)-(1/N_)*(ONE_*ONE_')
MAT R2OP_=(YHAT_'A_*Y_)**2/((YHAT_'A_*Y_)*(Y_'A_*Y_))
PRINT DW_ VN_ RHO_ ESUM_ SIG2_ EABS_ R2OP_
* NOW FOR THE RUNS TEST
MAT DUME_=DUM(E_)
MAT N1_=DUME_'ONE_
MAT N2_=DUM(-E_)'ONE_
MAT EN_=(2*N1_*N2_)/(N1_+N2_) +1
*PRINT EN_
MAT SN_=SQRT((2*N1_*N2_*(2*N1_*N2_-N1_-N2_))/((N1_+N2_)**2*(N1_+N2_-1)))
*PRINT SN_
* GET THE NUMBER OF RUNS
SAMPLE 2 N_
GENR DIFF_=DUME_.NE.LAG(DUME_)
SAMPLE 1 N_
MATRIX NRUNS_=DIFF_'ONE_ +1
MAT NORMSTA_=(NRUNS_-EN_)/SN_
PRINT NRUNS_ N1_ N2_ NORMSTA_
* NOW FOR THE SKEWNESS AND KURTOSIS
MATRIX S1_=E_'ONE_/N_
MATRIX S2_=(E_**2)'ONE_/N_
MATRIX S3_=(E_**3)'ONE_/N_
MATRIX S4_=(E_**4)'ONE_/N_
GEN1 M2_=S2_-S1_**2
GEN1 M3_=S3_-3*S1_*S2_+2*S1_**3
GEN1 M4_=S4_-4*S1_*S3_+6*S1_**2*S2_-3*S1_**4
GEN1 K2_=N_*M2_/(N_-1)
GEN1 K3_=N_**2*M3_/((N_-1)*(N_-2))
GEN1 K4_=N_**2*((N_+1)*M4_-3*(N_-1)*M2_**2)/((N_-1)*(N_-2)*(N_-3))
GEN1 G1_=K3_/(K2_**1.5)
GEN1 G2_=K4_/(K2_**2)
GEN1 SG1_=SQRT(6*N_*(N_-1)/((N_-2)*(N_+1)*(N_+3)))
GEN1 SG2_=SQRT(24*N_*(N_-1)**2/((N_-3)*(N_-2)*(N_+3)*(N_+5)))
PRINT G1_ SG1_ G2_ SG2_
* THE ONLY THING MISSING IS THE CHI-SQUARE GOODNESS OF FIT TEST
* NOT DONE HERE BECAUSE IT IS DIFFICULT TO GET RESIDUALS IN GROUPS
DELETE / ALL_
SET DOECHO
PROCEND
SET ECHO