Thanks professor! You always helps a lot!

On Mon, Nov 17, 2008 at 8:36 PM, Roger Bivand <Roger.Bivand@nhh.no> wrote:

> On Mon, 17 Nov 2008, Raphael Saldanha wrote:
>
>  Hi!
>>
>> Running some models, I'm having, pratically, the same results with the
>> models *spautolm(TX07 ~ X35A39 + TXPIB05, data=mg, family="SAR",
>> listw=rook_Ww)* and *errorsarlm(TX07 ~ X35A39 + TXPIB05, data=mg,
>> listw=rook_Ww)*. And looking the help don't helpe a lot... so, what are
>> the
>> basically differences between spautolm with SAR and errorsarlm, and what
>> conclusions can I reach with similar results?
>>
>
> spautolm() is a re-implementation of errorsarlm(), adding support for
> weights and for CAR and SMA. So the "similarity" of results is by design,
> they are doing exactly the same thing, but written in a more general way in
> spautolm(). There are differences in the summary methods, so the model
> output looks a bit different, but only in appearance and internal structure,
> not in the methods being implemented.
>
> Hope this helps,
>
> Roger
>
>
>
>>  summary(mg_sar)
>>>
>>
>> Call: spautolm(formula = TX07 ~ X35A39 + TXPIB05, data = mg, listw =
>> rook_Ww,     family = "SAR")
>>
>> Residuals:
>>    Min       1Q   Median       3Q      Max
>> -17.4249  -3.2110  -1.3689   1.7380  47.3231
>>
>> Coefficients:
>>            Estimate Std. Error z value Pr(>|z|)
>> (Intercept) -2.668712   2.999516 -0.8897 0.373619
>> X35A39       1.332412   0.417628  3.1904 0.001421
>> TXPIB05     -0.055142   0.024987 -2.2068 0.027326
>>
>> Lambda: 0.70216 LR test value: 348.09 p-value: < 2.22e-16
>>
>> Log likelihood: -2859.839
>> ML residual variance (sigma squared): 42.561, (sigma: 6.5239)
>> Number of observations: 853
>> Number of parameters estimated: 5
>> AIC: 5729.7
>>
>> ############
>>
>>  summary(mg_errorsar)
>>>
>>
>> Call:errorsarlm(formula = TX07 ~ X35A39 + TXPIB05, data = mg, listw =
>> rook_Ww)
>>
>> Residuals:
>>    Min       1Q   Median       3Q      Max
>> -17.4249  -3.2110  -1.3689   1.7380  47.3231
>>
>> Type: error
>> Coefficients: (asymptotic standard errors)
>>            Estimate Std. Error z value Pr(>|z|)
>> (Intercept) -2.668712   2.999516 -0.8897 0.373619
>> X35A39       1.332412   0.417628  3.1904 0.001421
>> TXPIB05     -0.055142   0.024987 -2.2068 0.027326
>>
>> Lambda: 0.70216 LR test value: 348.09 p-value: < 2.22e-16
>> Asymptotic standard error: 0.030286 z-value: 23.185 p-value: < 2.22e-16
>> Wald statistic: 537.52 p-value: < 2.22e-16
>>
>> Log likelihood: -2859.839 for error model
>> ML residual variance (sigma squared): 42.561, (sigma: 6.5239)
>> Number of observations: 853
>> Number of parameters estimated: 5
>> AIC: 5729.7, (AIC for lm: 6075.8)
>>
>>
>>
> --
> Roger Bivand
> Economic Geography Section, Department of Economics, Norwegian School of
> Economics and Business Administration, Helleveien 30, N-5045 Bergen,
> Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
> e-mail: Roger.Bivand@nhh.no
>
>


-- 
Atenciosamente,

Raphael Saldanha
saldanha.plangeo@gmail.com

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