b Program is for joint estimation of common mean and individualXb variances for two independent normal populations. See "Jointb Estimation of the Parameters of Two Normal Populations" in J.b American Statistical Association, June 1962, v. 57, pp. 446 -.c 454. I have added (ad hoc) an estimate of true variance. Allrc the rest is rigorous.----Mark Aldon Weiss August 9, 1984c MAXNUMIT% dc M(MAXNUMIT%), WX(MAXNUMIT%), WY(MAXNUMIT%)ccc( () "G" () () "0" () "U" ()c2d<dF " What is nx"; NX% 7dP " What is ny"; NY%TdZ " What is x-bar"; XBARqdd " What is y-bar"; YBARdn " What is Sx-squared"; SX2dx " What is Sy-squared"; SY2dM() (NX%SY2XBAR NY%SX2YBAR) (NX%SY2 NY%SX2)dd>e " You are allowed a maximum of ",MAXNUMIT%," iterations."{e " How many iterations do you want ";NUMIT%eee " M0 is ", M()e e " M0 is ", M()ee R%  NUMIT% f WX(R%) NX% ( SY2 ( YBAR M(R%) ) )Bf WY(R%) NY% ( SX2 ( XBAR M(R%) ) )f M(R%) (WX(R%)XBAR WY(R%)YBAR) (WX(R%) WY(R%))f " Wx",R%," is ",WX(R%)f" " Wy",R%," is ",WY(R%)f, " M",R%," is ",M(R%)f6 g@ " Wx",R%," is ",WX(R%)7gJ " Wy",R%," is ",WY(R%)WgT " M",R%," is ",M(R%)`g^ vgc MLIMIT M(R%)gh R%grSXI2 SX2 (XBAR MLIMIT)g|SYI2 SY2 (YBAR MLIMIT)g " Sx(I)-squared is ", SXI2h " Sy(I)-squared is ", SYI2(h " Sx(I)-squared is ", SXI2Ih " Sy(I)-squared is ", SYI2Sh : hVARIANCE (NY%(MLIMITXBAR)SYI2 NX%(MLIMITYBAR)SXI2) (NY%(MLIMITXBAR) NX%(MLIMITYBAR))h " Estimate of VARIANCE of final mean = ", VARIANCE8i " Estimate of VARIANCE of final mean = ", VARIANCE>iOi () "@"ate of VARIANCE of final mean = ", VARIANCE8i " Estimate of VARIANCE of final mean = ", VARIANCE>iOi (