proc spatialreg optimization failure

[Kyungjae]

I used proc spatialreg to analyze spatial econometrics model.

However, error messages kept showing up depending on model or data. "Opimization failed. Interpret the estimates with care" or 

"Optimization cannot improve the function value". In addition, although the message 'Algorithm converged' comes out, standard error, t value, and p value don`t appear. 

I specified quasi-Newton method and I specified maximum number of iterations as 1000.

Algorithm converged.

Parameter EstimatesParameter DF Estimate StandardError t Value ApproxPr > |t|Interceptpopf_rateacadoldfemalecollegemighouse_1ataxtrain_lambda_sigma2Restrict1

1	12675	148.614569	85.29	<.0001
1	32.448024	0.170667	190.12	<.0001
1	505.773196	139.973396	3.61	0.0003
1	-585.435224	12.982785	-45.09	<.0001
1	214.707052	12.250951	17.53	<.0001
1	-499.383547	12.682656	-39.38	<.0001
1	214.837050	1.364687	157.43	<.0001
1	-240.843630	0.983443	-244.90	<.0001
0	-199.938586	.	.	.
0	176.465831	.	.	.
1	98.594504	3.551837	27.76	<.0001
1	1629.535839	152.198891	10.71	<.0001
0	1.000000	.	.	.
1	11625708	0.255397	4.552E7	<.0001
-1	94905077	.	.	. *

ERROR: Optimization failed. Interpret the estimates with care.

Parameter EstimatesParameter DF Estimate StandardError t Value ApproxPr > |t|Interceptpopf_rateacadoldfemalecollegemighouse_1ataxtrain_rho_lambda_sigma2

1	4877.620429	5802.227026	0.84	0.4005
1	27.446622	1.054131	26.04	<.0001
1	-738.228100	161.714703	-4.57	<.0001
1	-460.278202	49.892925	-9.23	<.0001
1	317.332993	23.506006	13.50	<.0001
1	-514.798669	37.320073	-13.79	<.0001
1	134.349259	93.345199	1.44	0.1501
1	-192.431771	19.548520	-9.84	<.0001
1	-172.167729	18.373370	-9.37	<.0001
1	221.460165	26.588296	8.33	<.0001
1	383.475678	26.552452	14.44	<.0001
1	1420.679084	299.021935	4.75	<.0001
0	0.377923	.	.	.
0	-3.805885	.	.	.
1	660740	74.384999	8882.71	<.0001

WARNING: Optimization cannot improve the function value.

Parameter EstimatesParameter DF Estimate StandardError t Value ApproxPr > |t|Interceptpopf_rateacadoldfemalecollegemighouse_1ataxtrain_lambda_sigma2Restrict1

0	5033.903709	.	.	.
1	31.303281	0.028436	1100.83	<.0001
1	569.039293	43.805973	12.99	<.0001
0	-527.967647	.	.	.
0	438.671229	.	.	.
0	-363.941741	.	.	.
0	84.402772	.	.	.
0	-110.553241	.	.	.
0	-86.368103	.	.	.
1	223.582940	2.153441	103.83	<.0001
0	381.665965	.	.	.
0	790.001959	.	.	.
0	1.000000	.	.	.
0	3031879	.	.	.
-1	81288778	.	.	. *

[SteveDenham]

Try to use </> to load the output, rather than cutting and pasting.  The former will preserve column id's, etc.  Then please also include your code and some information about the dataset (response variable, number of records, etc.).  All I can say is that it might (stressing might) be that your model is over-parameterized for the amount of data.  Another possibility is multi-collinearity.

SteveDenham