Re: AI-GEOSTATS: Log transformation and zeros

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• ... some 0 values. When I log-trans I have to translate the values by hading some value. I guess you mean you have to do something arbitrary about the zeros
Message 1 of 8 , Oct 2, 2002
>Hi
>
>I'm analysing fisheries data (number of fish caught per hour) and I have
some 0 values. When I log-trans I have to translate the values by hading
some value.

I guess you mean you have to do something arbitrary about the zeros before
the log transform. The delta distribution is a generalization of the
lognormal for the presence of zeros. See:
Pennington M. 1983. EFFICIENT ESTIMATORS OF ABUNDANCE FOR FISH AND PLANKTON
SURVEYS. Biometrics 39:281-286.
If you are interested, i have template worksheets that compute the
statistics from delta/lognormal distributions, including confidence bounds,
by using Land's theory of linear combinations of the normal mean and
variance.
You can speak in Spanish to me if you feel more comfortable.
Saludos
Rubén
http://webmail.udec.cl

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• Hi I was investigating my data and it is possible to identifie areas of zeros on the outside limits of the distribution, so it can be possible to model the
Message 2 of 8 , Oct 3, 2002
Hi

I was investigating my data and it is possible to identifie areas of
zeros on the outside limits of the distribution, so it can be possible
to model the spatial behaviour in two steps.

My guess is that I can simple reduce the kriging area to leave the zero
area out.

My doubt is how to model boundaries. I'm sure this is a common problem,
so if you can give me some references I'll look forward to find them.

Thanks and regards

EJ

On Wed, 2002-10-02 at 19:33, Donald E. Myers wrote:
> Adding a constant to all values will shift the distribution but will not
> change its shape. If the fraction of zeros is large then you will likely
> not have a lognormal distribution and hence taking logs may not solve
> the problem. If you intend using kriging (after applying a log
> transform) then you will have to worry about the bias correction when
> you re-transform, to do that the theoretical solution requires
> multivariate lognormality (univariate is not sufficient).
>
> You might want to look at the spatial pattern of the zeros, i.e., is it
> plausible to separate the data set spatially and have most of the zeros
> in only one region?
>
> Donald E. Myers
> http://www.u.arizona.edu/~donaldm
>
> Ernesto Jardim wrote:
>
> >Hi
> >
> >I'm analysing fisheries data (number of fish caught per hour) and I have
> >some 0 values. When I log-trans I have to translate the values by hading
> >some value.
> >
> >My question is which value is the best ? is there any works about this ?
> >
> >I usually had 1 so that I get values between 0 and infinite (no negative
> >value) but I have doubts about it.
> >
> >Regards
> >
> >EJ
> >
> >
> >
> >
> >--
> >* To post a message to the list, send it to ai-geostats@...
> >* As a general service to the users, please remember to post a summary of any useful responses to your questions.
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> >
> >
>

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• ... on the outside limits of the distribution, so it can be possible to model the spatial behaviour in two steps. ... area out. ... if you can give me some
Message 3 of 8 , Oct 3, 2002
>Hi
>
>I was investigating my data and it is possible to identifie areas of zeros
on the outside limits of the distribution, so it can be possible to model
the spatial behaviour in two steps.
>
>My guess is that I can simple reduce the kriging area to leave the zero
area out.
>
>My doubt is how to model boundaries. I'm sure this is a common problem, so
if you can give me some references I'll look forward to find them.
>
>Thanks and regards
>
>EJ

Intrinsic geostatistics, the theory based on random functions, does not
allow for 'boundary effects'. There should be no interaction between the
random variable and its field (in practice, no decrease of density near the
borders). On the other hand, transitive geostatistics, the theory based on
purposive randomization, does allow for border effects and estimation of
boundaries, which may fall anywhere between zero and non-zero observations.
The difference between intrinsic and transitive geostatistics is as basic
as the difference between model-unbiased and design-unbiased statistical
inference.
See
Petitgas. 1993. Geostatistics for fish stock assessmens: a review and an
acoustic application. ICES J Mar Sci 50:285-298.
Petitgas and Lafont. 1997. EVA2: estimation variance. Version 2. A
geostatistical software on Windows 95 for the precision of fish stock
assessment surveys. ICES CM 1997/Y:22.

Rubén
http://webmail.udec.cl

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• while possibly outside the domain of your original question, I suspect that you may be able to treat your yield data as integers by treating the denominator as
Message 4 of 8 , Oct 3, 2002
while possibly outside the domain of your original question, I suspect that
you may be able to treat your yield data as integers by treating the
denominator as an offset variable (as a technicality, I'd argue that, even
after dividing by a constant, your data remain discrete--just not
integers). this common technique would appear to take you back into the
discrete world that Nicholas touched on. brian

****************************************************************
Brian Gray
USGS Upper Midwest Environmental Sciences Center
575 Lester Avenue, Onalaska, WI 54650
ph 608-783-7550 ext 19, FAX 608-783-8058
brgray@...
*****************************************************************

Ernesto Jardim
<ernesto@ipimar. To: Nicholas Lewin-Koh <nikko@...>
pt> cc: Mailing List AI-Geostats <ai-geostats@...>
Sent by: Subject: Re: AI-GEOSTATS: Log transformation and zeros
ai-geostats-list
@...

10/02/2002 09:47
AM
to Ernesto
Jardim

Hi

The data are not discrete. We collect number per hour, so it's a yield !

Thanks

EJ

On Wed, 2002-10-02 at 15:27, Nicholas Lewin-Koh wrote:
> Hi,
> If the data are counts, ie integer number of fish and not tons, you
> might want to try a discrete model such as a negative binomial or
> Poisson. I have listed some references below, the top two have a more
> Bayesian flavor.
>
> Nicholas
>
>
> Alexander, N., Moyeed, R., Stander, J. (2000). Spatial modelling of
> individual-level parasite counts using the negative binomial
> distribution, Biostatistics, 2000, 1, 453-463.
>
> Diggle, P. J., Moyeed, R. A., Tawn, J. A. (1998). Model-based
> geostatistics (with discussion), J. R. Statist. Soc. C, 47, 299-350.
>
> Gotway, C.A., Stroup, W.W. (1997) A Generalized Linear Model Approach
> to Spatial Data Analysis and Prediction. Journal of Agricultural, Bio-
> logical and Environmental Statistics 2(2), pp. 157­178.
>
>
> On Wed, 2002-10-02 at 19:24, Ernesto Jardim wrote:
> > Hi
> >
> > I'm analysing fisheries data (number of fish caught per hour) and I
have
> > some 0 values. When I log-trans I have to translate the values by
> > some value.
> >
> > My question is which value is the best ? is there any works about this
?
> >
> > I usually had 1 so that I get values between 0 and infinite (no
negative
> > value) but I have doubts about it.
> >
> > Regards
> >
> > EJ
> >
> >
> >
> >
> > --
> > * To post a message to the list, send it to ai-geostats@...
> > * As a general service to the users, please remember to post a summary
of any useful responses to your questions.
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> >
> >
> >
>

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