00283 Na1efd990e69e725fd6ed704b186932

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Experimental Design Models with Random Components

Dependent Yariable: Y

Iteration	Objective	Var(DAY) Var (Error)	Var (SITE)	Var (DAY*SITE)
0	-752.89961393	0.00223155 0.00374071	0.00024649	0.00029911
1	-752.96220709	0.00193678 0.00376089	0.00022934	0.00031365
2	-752.96299614	0.00193305 0.00376594	0.00022467	0.00030855
3	-752.96303827	0.00192986 0.00376720	0.00022479	0.00030699
4	-752.96304069	0.00192939 0.00376752	0.00022473	0.00030660
5	-752.95304083	0.00192927 0.00376759	0.00022472	0.00030651
6	-752.96304084	0.00192924 0.00376761	0.00022471	0.00030648
7	-752.96304084	0.00192924 0.00376761	0.00022471	0.00030648

Coveragence criteria met.

Asymptotic Covariance Matrix of Estimates

Var(DAY) Var (SITE) Var(DAY*SITE) Var (Error)

Var(DAY)

1.3677823E-6

1.5525707E-8

-2.910763E-8

-7.16038E-13

Var (SITE) 1.5525707E-8 7.6657298E-8 -1.89602E-8 -8.34025E-14

Var (DAY*SITE) -2.910763E-8 -1.89602E-8 1.4792709E-7 -6.759525E-8

Var (Error) -7.16038E-13 -8.34025E-14 -6.75952E-8 2.7037913E-7

Figurę 2. Maximum Likclihood Variance Components Estimation

Procedurę.