- Netsy/Intesys - L. Ongaro wrote:
>

--

> >>>>

>

> Return-Path: <carli@...>

> X-Sender: MASSIMO CARLI <carlim@...>

> Date: Thu, 15 May 1997 15:53:04 +0200

> To: nonna@..., 00492aaa@...,

> puliti@...,

> ruggeri@..., giudici@...,

> bertoncello@..., alm@...,

> deriso@...,

> garavelli@..., mike@...,

> MAURI@..., netsy@..., jag@...,

> a922ts@..., visea@...

> From: Massimo Carli <carli@...>

> Subject:

>

> >From owner-java-it@... Thu, 15 May 1997

> 10:21:26

> From: "Filippo Bobbi" <f.bobbi@...>

> To: "Java-it" <java-it@...>

> Subject: Java-IT: I: (Fwd) Dev-IT: Appello Urgente

> Date: Thu, 15 May 1997 10:03:37 +0200

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> Sender: owner-java-it@...

> Reply-To: java-it@...

>

> ----

> Da: Bertellotti Alessandro <abertel@...>

> A: dojo@...; barmario@...

> Data: gioved 15 maggio 1997 8.20

> Oggetto: (Fwd) Dev-IT: Appello Urgente

>

> > Appello Urgentissimo - VERY URGENT APPEAL

> >

> > Urge aiuto per una bambina italiana di sei anni Francesca

> De Lunas

> > FRANCESCA DE LUNAS IS A 6 YRS OLD DAUGHTER WHO URGENTLY

> NEEDS HELP.

> >

> > ricoverata presso il reparto rianimazione dell'ospedale

> Brotzu di

> > Cagliari

> > (Sardegna-Italia) Dott. Pettinao.

> > SHE'S NOW UNDER THERAPY BY DR. PETTINAO AT THE "REPARTO

> RIANIMAZIONE"

> > [REANIMATION DEPT.],

> > OSPEDALE BROTZU, CAGLIARI (SARDINIA, ITALY)

> >

> > La bambina presenta una sindrome caratterizzata da:

> > SHE SHOWS A SYNDROME WHICH PECULIARITIES ARE:

> >

> > - ipercoagulazione del sangue;

> > BLOOD HYPERCOAGULATION

> >

> > - trombi che si formano in circa 15 secondi di colore

> rosso con nucleo

> > bianco

> > di lunghezza di circa 2-3 cm.

> > RED THROMBI WITH WHITE NUCLEUS, ABOUT 2-3 CM LONG, WHICH

> FORM IN 15

> > SECS.

> >

> > Alla bambina e' stata gia' amputata la gamba sinistra e,

> finora non e'

> > stato possibile effettuare diagnosi di alcun tipo.

> > THE DAUGHTER HAS ALREADY BEEN AMPUTATED THE LEFT LEG. IT

> HAS NOT BEEN

> > POSSIBLE

> > TO MAKE ANY DIAGNOSIS UNTIL NOW.

> >

> > Chiunque sia in grado di ipotizzare una diagnosi o di

> riconoscerla

> > si metta urgentemente in contatto con le seguenti e-mail:

> > ANYBODY ABLE TO MAKE A DIAGNOSIS OR RECOGNIZE THIS DISEASE

> PLEASE GET

> >IN

> > TOUCH

> > URGENTLY BY E-MAIL TO THE FOLLOWING ADDRESSES:

> >

> > <mailto:lukrezia@...>lukrezia@...

> >

> > <mailto:stefania@...>stefania@...

> >

> > schintu@...

> >

> > <mailto:psico@...>psico@...

> > *********************************

> > THANK YOU VERY MUCH FOR YOUR COOPERATION

> >

> > Grazie per l' attenzione.

> >

> > By

> >

> >

> --------------------------------------------------------------

>

> >

> > Vi prego di forwardare questa e-mail in tutte le mailing

> list a cui

> > siete

> >

> > iscritti... per favore...

> >

> > --

> > Massimo D'Eramo

> > Vice Presidente

> > Grande Associazione Sterratisti - ROMA

> >

> > <http://www.ics.it/gas>http://www.ics.it/gas

> > e-mail:<<mailto:gas@...>gas@...>

>

> ************************************************************************

>

> * Bertellotti Alessandro * IRC Nick (on EFNET): Roccia *

> * mailto:abertel@... * PowWow: abertel@...

> *

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>

> ++++++++++++++++++++++++++++++++++++++++++++++++

> Ing. Massimo Carli

> Java and Internet Developer

> tel. +39 425 362885

> (0338) 7372320

> email : carlim@...

> carli@...

> Collaboratore Mokabyte

> http://www.programmers.net/Riviste/moka/current/

> +++++++++++++++++++++++++++++++++++++++++++++++++

>

> <<<<

>

> Ing. Luciano Ongaro

> Netsy

> software for the network computing age

> a division of Intesys Srl

> via Latason, 5

> 36030 CALDOGNO (VICENZA) - Italy

> tel +39 444 905440 fax +39 444 905441

> Email:<mailto:netsy@...> Web <http://www.netsy.it>

++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Christiane Boehner

Joint Research Centre of the European Commission

Institute for Systems,Informatics and Safety

Tecnology Assessment

T.P. 361, I - 21020 Ispra (VA)

++ ++ ++ ++

phone: ++39 332 789517

fax: ++39 332 789394

e-mail:christiane.boehner@...

http://taws03.jrc.it/epu/christiane/boehner.html

++++++++++++++++++++++++++++++++++++++++++++++++++++++++

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DO NOT SEND Subscribe/Unsubscribe requests to the list! - There have been some attempts at "adaptive" interpolation,

e.g. refer papers by Wong et al at the University of New

South Wales on the use of RBF networks for spatial

prediction. Initial attempts have been at optimizing

RBF constants (analogous to the "range") and type

of RBF (analogous to the variogram type) which differ

from neighborhood to neighborhood. Anisotropy ratios

can presumably be optimized, although CPU cyles can

potentially be huge, since minimzation of some sort

of "error" function would be required (cross-validated

residuals?) as we go from one prediction location

to the other. Practically speaking, it's difficult

enough to get a well-defined variogram if data are

insufficient.

Regards,

Syed

Bharat Lohani wrote:>

--

> Hi,

>

> Please could you help me with....

>

> 1. Any reference about any adaptive interpolation method?

> ( Adaptive means which interpolates considering the local

> anisotropy. The kriging takes the global

> varigram model, which might not be true for local

> variations ( am I correct ?).)

>

> 2. I need to carry out some neighborhood operations with the

> data which is not in grid. This requires searching the

> full data set (approx. 1 M points ) evertime to find the

> points in the neighborhood of known locations. The super

> block search in GSLIB is a clever implementation for

> the same. However, I am looking for a code in c, if

> available, for super block search or anyother parallel

> algorithm, which might save my time of converting the

> GSLIB algorithm to c.

>

> Thanks in advance.

>

> Bharat.

> --

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DO NOT SEND Subscribe/Unsubscribe requests to the list! - Now that I think about it I am not sure that

it would be practical to construct a rose

diagram for each pred. location, experimenting

with different angular and lag tolerances and

directions in order to derive some sort of anisotropy

ratio, and then fit the variogram models automatically,

and then make a prediction, move on to a different

search neighborhood and repeat the whole process.

I would take exception to fitting variograms

automatically, and an anisotropic one at that;

any attempt to automate an art smacks of Alice-in-

Wonderland kind of geostatistics.

Regards,

Syed

Bharat Lohani wrote:>

--

> Hi,

>

> Please could you help me with....

>

> 1. Any reference about any adaptive interpolation method?

> ( Adaptive means which interpolates considering the local

> anisotropy. The kriging takes the global

> varigram model, which might not be true for local

> variations ( am I correct ?).)

>

> 2. I need to carry out some neighborhood operations with the

> data which is not in grid. This requires searching the

> full data set (approx. 1 M points ) evertime to find the

> points in the neighborhood of known locations. The super

> block search in GSLIB is a clever implementation for

> the same. However, I am looking for a code in c, if

> available, for super block search or anyother parallel

> algorithm, which might save my time of converting the

> GSLIB algorithm to c.

>

> Thanks in advance.

>

> Bharat.

> --

> *To post a message to the list, send it to ai-geostats@....

> *As a general service to list users, please remember to post a summary

> of any useful responses to your questions.

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DO NOT SEND Subscribe/Unsubscribe requests to the list! - Melanie Wall wrote:

> I have a question about the parameter space of the rho

Dear Melanie,

> parameter in a SAR model.

>

> Consider the following two dispersion matrices Sigma for Spatial

> Regression Models. Let W be a symmetric neighbor matrix.

>

> CAR: Sigma = (I - rho W)^{-1}

> SAR: Sigma = [t(I - rho W) %*% (I - rho W)]^{-1}

>

> Everywhere I look, people discuss the restrictions on rho so that (I - rho

> W) is positive definite. It is very straightforward to show the

> conditions on rho that satisfy this condition as they are related to the

> eigenvalues of W. Obviously for the CAR model, we should be restricting

> ourself to (I -rho W) positive definite, but, in the SAR model there is no

> need to restrict (I - rho W) to be positive definite, instead all we need

> is invertibility (i.e. non singular). The problem with this is, it is not

> much of a restriction because all it requires is that rho does not = the

> inverse of any of the eigenvalues of W. Thus there is really no upper

> bound on what rho can be to ensure (I- rho W) to be invertible

> (but not positive definite). Has anyone ever seen any discussion of

> this?

>

> I have already run across two examples where if I use the CAR model in S+

> Spatial Stat's slm() function, I get a rho value that is less than

> 1/(max(eigenvalue of W) (as it should be to ensure (I - rho W) positive

> definite). But then, when I run a SAR model using the exact same data I

> get a rho value outside the range that would ensure positive definiteness.

> That is (I - rho W) is invertible but not positive definite. It seems to

> me that it is hard to interpret an estimated rho if there is no upper

> bound on what it could be.

>

> Does anyone have any comments about this topic.

>

> Thanks

> MW

>

> -----------------------

> Melanie Wall, Ph.D.

> Division of Biostatistics

> A460 Mayo Building Box 303

> 420 Delaware Street S.E.

> Minneapolis, MN 55455

> (612)625-2138

> melanie@...

Usually, the underlying process Z(x,y) admitting a SAR representation is assumed

to be

covariance stationary under translation of (x,y). This can be shown to be the

case if a

certain polynomial in complex variables is non-zero on the unit complex circle.

This imposes conditions on the admissible values for rho. For instance, in 2D,

if the same rho

is used in each direction, then |rho|<1/4.

Two good references are Whittle, P. (1954), ``On stationary processes in the

plane'', Biometrika,

41, 434-449, as well as Ali, M.M. (1979), ``Analysis of stationary

spatial-temporal processes:

Estimation and prediction'', Biometrika, 66, 515-518.

You might also take a look at the extended abstract of our talk:

de Luna, X., Genton, M. G., (1999): "Indirect inference for spatio-temporal

autoregression models",

Proceedings of the Workshop Spatial-temporal modeling and its application,

Leeds, UK, 61-64

(edited by K.V. Mardia, R.G. Aykroyd and I.L. Dryden).

It consists of a new simulation-based estimation procedure for the more general

STAR

models, allowing for different rho's in each space direction, and time, as well

as for robust estimates.

We are currently writing the full paper about this topic.

Regards

Marc Genton

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

_/ Marc G. Genton

/_/ _/ / / _______/ Department of Mathematics, 2-390

/ _/ _/ / / / 77 Massachusetts Avenue

/ _/ / / / Cambridge, MA 02139-4307

/ / / /

/ / / / E-mail: genton@...

_/ _/ _/ _/ _/ _/ _/ http://www-math.mit.edu/~genton

Phone: (617) 253-4390

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Fax: (617) 253-4358

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

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DO NOT SEND Subscribe/Unsubscribe requests to the list! - Thanks for the comments in response to my question about the SAR model.

One comment was about restricting rho such that the the underlying process

Z(x,y) is covariance stationary. This brings up an interesting issue

because, I think, in general it is not possible. In general, the

covariance matrix (Sigma) resulting from a SAR specification with neighbor

matrix W

Sigma = [t(I - rho W) %*% (I - rho W)]^{-1}

is NOT going to be covariance stationary no matter how we restrict

rho. Isn't it true that W has to have a very special form in order to be

able to put restrictions on rho that ensure Sigma is covariance

stationary. I believe W must be symmetric and have equal neighbors for

each location for there to be any hope of Sigma being covariance

stationary. Haining (1990 p. 82) talks about how Sigma is not usually

representing a covariance stationary process.

The question I asked in my last e-mail was about the restriction on rho

needed to make Sigma positive definite. But, when I asked that, I was not

aware of this seemingly bigger problem of lack of second order

stationarity in Sigma that occurs for most W. So now I have a new

question, Should I care? Is this a problem? This sort of model has

obviously been used for a long time, do people just ignore the fact that,

in general, Sigma is not going to represent a stationary process?

I have just recently started to look at this sort of model in the spatial

setting and it is clearly not a straightforward extension of what I know

about time series models.

Thanks for any replies.

Melanie

-----------------------

Melanie Wall

Division of Biostatistics

A460 Mayo Building Box 303

420 Delaware Street S.E.

Minneapolis, MN 55455

(612)625-2138

melanie@...>

--

> Dear Melanie,

>

> Usually, the underlying process Z(x,y) admitting a SAR representation is assumed

> to be

> covariance stationary under translation of (x,y). This can be shown to be the

> case if a

> certain polynomial in complex variables is non-zero on the unit complex circle.

> This imposes conditions on the admissible values for rho. For instance, in 2D,

> if the same rho

> is used in each direction, then |rho|<1/4.

> Two good references are Whittle, P. (1954), ``On stationary processes in the

> plane'', Biometrika,

> 41, 434-449, as well as Ali, M.M. (1979), ``Analysis of stationary

> spatial-temporal processes:

> Estimation and prediction'', Biometrika, 66, 515-518.

>

> You might also take a look at the extended abstract of our talk:

> de Luna, X., Genton, M. G., (1999): "Indirect inference for spatio-temporal

> autoregression models",

> Proceedings of the Workshop Spatial-temporal modeling and its application,

> Leeds, UK, 61-64

> (edited by K.V. Mardia, R.G. Aykroyd and I.L. Dryden).

> It consists of a new simulation-based estimation procedure for the more general

> STAR

> models, allowing for different rho's in each space direction, and time, as well

> as for robust estimates.

> We are currently writing the full paper about this topic.

>

> Regards

>

> Marc Genton

>

>

>

>

> $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

>

> _/ Marc G. Genton

>

> /_/ _/ / / _______/ Department of Mathematics, 2-390

> / _/ _/ / / / 77 Massachusetts Avenue

> / _/ / / / Cambridge, MA 02139-4307

> / / / /

> / / / / E-mail: genton@...

> _/ _/ _/ _/ _/ _/ _/ http://www-math.mit.edu/~genton

> Phone: (617) 253-4390

> MASSACHUSETTS INSTITUTE OF TECHNOLOGY Fax: (617) 253-4358

>

> $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

>

>

>

>

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