Dear Rober, thank you very much for all the explanation! Of course it did
clarify a lot. I will also take a look at your suggestion about leading
with the zero-inflation menance.

FABRICIO

2012/4/5 Roger Bivand <Roger.Bivand@nhh.no>

> On Thu, 5 Apr 2012, Fabricio Vasselai wrote:
>
>  Dear list,
>>
>> Maybe someone can shed some light on this error. I have a dataset with
>> thousands of candidates with electoral support per city. I wrote a R
>> script
>> to calculate both Moran.test and Moran.MC (99999 iterations), and also
>> Geary C test.
>> The script run very fine, but at the end I have noticed that a few of my
>> cases (candidates) didn't have a result to Moran.test's standard deviation
>> and p-value. All estimates and values were normal for Moran.MC and Geary's
>> C.
>>
>> The problem seems to be the following error:
>>
>> Moran's I test under randomisation
>>
>
> Under randomisation, the variance is formed in the usual way, but adjusted
> downward by a term multiplied by the kurtosis. It looks as though extreme
> values of kurtosis can generate this result (negative variance). If you try
> randomisation=FALSE, you assume normality, with randomisation=TRUE, the
> variance formula tries to adjust for departures from normality, but
> obviously here does not succeed. The kurtosis used is equivalent to:
>
> library(e1071)
> kurtosis(votoscandidato, type=1)+3
>
> and it appears to tip when the kurtosis is greater than N. Next, the
> squared expectation is subtracted, which could push a marginally positive
> intermediate result negative. The conclusion is that your data have a
> distribution that is so non-normal (skew and kurtosis) that this analytical
> correction is being defeated.
>
> A similar correction is made in geary.test(), but the term multipled by
> the kurtosis is itself smaller, so the test could also fail, but with even
> more severe kurtosis. The MC test is not failing because no analytical
> correction is used, not because of the number of iterations. However, I
> think that the test results in the presence of zero-inflation will be
> misleading, and that you may actually need to use the parametric bootstrap
> approach from DCluster, its accompanying article, and with reference to
> Waller & Gotway (2004).
>
> Hope this clarifies,
>
> Roger
>
>
>
>
>> data:  votoscandidato
>> weights: UF.listw.W
>>
>> Moran I statistic standard deviate = NaN, p-value = NA
>> alternative hypothesis: two.sided
>> sample estimates:
>> Moran I statistic       Expectation          Variance
>>    5.723951e-03     -2.409639e-03     -8.785771e-09
>> Mensagens de aviso perdidas:1: In sqrt(VI) : NaNs produzidos2: In
>>
>> moran.test(x = votoscandidato, listw = UF.listw.W, zero.policy = TRUE,
>> :
>>  Out-of-range p-value: reconsider test arguments
>>
>>
>>
>>
>>
>> I checked the source data and those cases with such an error seem to
>> be cases with a lot of zero votes in many of the cities. But the same
>> problem does not affect Geary's C or Moran.MC (probably because of the
>> high number of iterations).
>>
>>
>>
>> Maybe this is the problem? Any help or tips will very much appreciated.
>>
>>
>>
>> Best regards,
>>
>>
>>
>> FABRICIO
>>
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>>
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>>
>>
> --
> Roger Bivand
> Department of Economics, NHH Norwegian School of Economics,
> Helleveien 30, N-5045 Bergen, Norway.
> voice: +47 55 95 93 55; fax +47 55 95 95 43
> e-mail: Roger.Bivand@nhh.no
>
>

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