>= Original Message From Isobel Clark <[EMAIL PROTECTED]> =
>Well said, Neil!
>Maybe we should have a debate on the list on what is
>and isn't acceptable to the general reading public?
>Gregoire does a great job of running this list but it
>is up to us to maintain the standards in our own
>= Original Message From "Digby Millikan" <[EMAIL PROTECTED]> =
>Hello,
> I have always lead the belief that it is worth while cleaning up a
variogram, but with OK a poor variogram
>model for normally distributed data will give superior results than inverse
distance methods, though with
>= Original Message From "Digby Millikan" <[EMAIL PROTECTED]> =
Digby:
Isobel has responded to your questions about my comments, but i may add
something of value
>Ruben,
>>Regarding lognormal data, if you are only interested in the mean of the
>>regionalized variable and its confidence
>= Original Message From [EMAIL PROTECTED] =
[snip]
>The aim of the work is to compare three sites representing
>pre-plantation/undisturbed conditions, 1st rotation plantation trees (Pinus
>radiata), and 2nd rotation trees. An area has been found where examples of
>these sites occur close
Gregoire Dubois wrote:
>
> On a 26th of April, 7 years ago, the first email was sent to the ai-geostats
> mailing list. It doesn't make me younger but nevertheless, I'm very happy to
> see that the list and the topics that are discussed are still very alive.
>
> Thanks a lot to all of you who co
were known. This might be justified since normally the sample
size (pairs of observations) is quite high when fitting the variogram
via weighted least squares, for instance. Any opinion on this and/or
references would be much welcome.
Thanks
Ruben Roa
--
* To post a message to the list, send it to
Chaosheng Zhang wrote:
[snip]
Hi Chaosheng:
A few points about log transforms. See below.
> The reason why I care about this issue is that there are at least two
> problems related to data transformation (in order to follow the normal
> distribution):
>
> (1) The measurement scale is reduce
>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 generaliza
>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
>Dear List:
>
>Does anyone know which method of variogram fitting (goodness of the fit)
the software Variowin use when adjusting a variogram model? Is it minimum
weights mean squares errors technique? I don't have the guide of this
software so I don't know this specification.
Variowin 2.2. uses w
Isobel did not write the careless paragraph about the central limit theorem
(CLT) Don replied to, as pointed out by Digby. I wish to add something to
what Don said about the conditions under which the CLT applies, and that
people usually miss in considering the universality of the CLT. See below.
>Dear all,
>
>The AIC is used to select the "best" model from a list
>of theoretical functions. I wonder if its necessary
>the models need to be fitted by the same method ?
Yes. The model must be fitted my maximum likelihood.
>Would it be possible to stress the AIC to select the
>"best" model fr
>suspect Ruben would note that, under a normal assumption, OLS and ML
coincide.
True, though i'd say that OLS is a particular case of MLE iff the process
being modelled is additive and the additive stochastic component is normal.
>also, I suspect that Ruben's comments also apply to REML
>results-
>>The algebraic expression for the AIC results from the bias in the maximum
log-likelihood of a model as estimator of the mean expected log-likelihood,
this bias being a function of the number of free parameters in the model.
So it only covers those models fitted by maximum likelihood.
>
>Please, l
Dear list members:
I run into problems when creating data files with Excel 2002 for use in
Variowin 2.2 Prevar2d module. Variowin says it finds an 'error while
reading file'. It happens also with old data files that i created with
Excel 97 and that worked fine under Windows 95 in Variowin 2.2. Howe
>If I understand your question correctly, you are trying to use an EXCEL
file as an input for Variowin Prevar. Obviously it won't work for several
reasons (a) Variowin uses the same file format as GEOEAS, a plain ASCII
file, (b) the data itself is in columns separated by spaces or commas, (c)
the v
Thanks to Pierre, Chris, Donald, Vassily and Tom for their suggestions in
my problem with GeoEas data files under W-XP. Saving the data file in
GeoEas format from Excel as formatted text space-delimited (*.prn)
(Pierre's suggestion) did allow to read and work the data in Variowin 2.21,
but alas! i'
>G'day all,
>
>I reckon we need to quantify the reliability of the kriging variance map.
Because sometimes its going to be an accurate map, and other times its
going to be way off the mark.
>
>Imagine the situation when there are two maps with similar kriging
variances. However when we look at the
>
>A couple of observations on your problem
>
>1. The kriging variances are computed, not estimated, hence in that sense
they are completely and perfectly "reliable"
IOW, the kriging variances are the objective functions to be optimized not
the parameters to be estimated (the latter ones are the
>Hi Ulrich
>
>I'm surprised we got mainly "pragmatic" answers to your question and would
have expected from statisticians and mathematicians more reactions about a
possible statistical heresy: the semivariogram model is fitted to an
experimental semivariogram which was obtained from a certain numbe
Mensaje Original
Asunto: Re: AI-GEOSTATS: Large sample size and normal distribution De:
"Ruben Roa Ureta" <[EMAIL PROTECTED]>
Fecha: Sat, 2 de Agosto de 2003, 5:22 pm
Para: "Chaosheng Zhang" <[EMA
> Hi,
>
> I'm not sure i agree with the idea that a test can be too powerful. This
is a common argument in simulation experiments, that because you can do an
infinite number of replicate simulations, somehow the differences
detected are not real. In fact, the differences are real. They may not
> Dear All,
>
> One week ago I posted a question about large n and normal distritbuion,
and have got several good replies from Isobel Clark, Ned Levine, Ruben Roa
Ureta, Thies Dose, Chris Hlavka, Donald Myers and Jeffrey Blume. Jeffrey
is perhaps not in the list, but I assume he has no o
> Hello everybody,
>
> I have several (maybe too simple) questions on geostatistics:
>
> 1. I would like to know where I can find any kind of detailed
> interpretation guide for the nugget effect. I know how to describe the
nugget effect in my words, but I don´t know how do it in scientific
english
> Hi,
>
> I am working on a set of soil data - pollution analysis. The data is
> not spatially correlated because there are outliers into the data.
> Since the data came from an old industrial site i suspect that the
> outliers are linked with point source pollution.
When i first started reading a
> Hi again,
>
> first of all big thanks to everyone who supported my last email -
question concerning the nugget effect.
>
> My question this time is as follows:
>
> Is there any mathematical measure, that provides information on the
> performance of a interpolation methods compared to the reality
Hi people:
I am looking for information (journal papers, reports, etc) about the
maximum likelihood estimation of variogram parameters and the total of a
single variable over the spatial field. My final purpose is to produce
profile likelihood plots of fish biomass. I know there is PhD thesis by
Ma
Hi:
Regarding my recent question, i received the replies listed below. Thanks
to all those who responded giving me useful hints.
Rubén
My question:
Hi people:
I am looking for information (journal papers, reports, etc) about the
maximum likelihood estimation of variogram parameters and the tot
> A couple of observations
>
> 1. Matern's thesis originally was published in Swedish but reprinted in
> English in 1986 by Springer-Verlag, the title is "Spatial Variation"
> (this appears in a statistics series)
Thanks, i noticed the publication in a biostatistics series and it's not
available
> Trevor,
>
> I always wonder what the value of testing significance of spatial
> correlation is, and never advise to do it. See, if data are spatial, it
> is extremely unlikely that they are spatially uncorrelated. Rejecting
> the test is usually only a matter of collecting sufficient evidence,
>
Some time ago i posted a question about the Matern family of correlation
functions for spatial data, because i have read in the GeoR papers that
that family allowed likelihood inference in geostatistics. There were
several good replies that i summarized. Then more good replies came
shortly. In para
Mensaje Original
Asunto: Re: AI-GEOSTATS: Detecting spatial autocorrelation in highly
nonnormaldata De: "Ruben Roa Ureta" <[EMAIL PROTECTED]>
Fecha: Wed, 26 de Noviembre de 2003, 7:32 pm
Para: "Yetta Jager&qu
> Hi everyone,
>
> I would appreciate any light in defining and separating Monte Carlo
> resampling techniques and bootstrapping techniques. In my search
> it seems that the two notions are more or less the same which
> puzzles me - i suppose if there are 2 different names, would be 2
> differ
Hi list members:
I am now embarked in a project of fish stock assessment in the Falklands
using both hydroacoustics and fish density data from trawling, and of
course i want to use geostatistics for data analysis. I read in ai-geostat
archives a discussion not long ago about coordinate transformati
Hi group:
Thanks for the replies about coordinate transformation near the poles
(that was some time ago but i went on a research cruise for 2 weeks and
couldn't reply in a timely manner). I gathered UTM is fine. Carmen Hervada
enlightened me by pointing out that variogram modelling requires metric
> Hi,
>
> I am working myself with pollution data in soils and i have very high
> values very close to very low values, and highly skewed
> distribution. I am more and more concerned with doing kriging on
> transformed data. This simply means we believe the data came
> from only one population. But
> Dear Isobel and all,
>
>
>
> This is an interesting topic. I appreciate the ideas of the software
> "MIX", but have not tried it yet. If somebody finds it "really" useful, I
> may have a try. My main concern is that one needs to define subpopulations
> prior to "separate" mixed populations, but t
> Dear list members,
>
> I am wrestling with particular dilemma regarding how to incorporate data
> collected without a design or probability basis into kriging estimators.
Kriging estimators of interpolated values on a grid coming from intrinsic
geostatistics do not depend on a sampling desing, i
Hi:
Has anyone obtained the profile likelihood of the mean (strict
stationarity for simplicity) of the stochastic process, with any
geostatistical software? This question is related to likelihood-based
geostatistics, rather than the more common distribution-free approach. The
closest in terms of s
> hello,
> I have a question about what is/should be typically done when kriging is
> used for spatial interpolation of a process X(z) where z gives spatial
> location (e.g. z=(x,y) with cartesian coordinates x,y) and X(z) has a
> skewed continuous distribution with nonnegative support. For instan
Hi:
Try GeoConv, it is free, runs in batch mode, and converts to many
different coordinate types. I use it for conversion of hundreds of
coordinate pairs with a few command lines and a few seconds of cpu time.
Its author, Eino Uikkanen, is a very kind person, always willing to help.
http://www.kolu
Hi:
I hope my question is not considered offtopic. It concerns
with an aspect of the mathematical theory of the spatial
autocorrelation function. In his 1954 Biometrika paper*, on
stationary processes in the plane, Whittle demonstrated that
the natural extension of the time series theory to spatial
> Hello list,
>
> I know that normality is not required to do geostatistical analysis of
> (georeferenced) data. Still I'm unable to find any publication that
> refers to this statement to which i can refer.
>
> Any suggestions?
Sure:
Ecker MD. 2003. Geostatistics: past, present and future. In
En
> Hi list,
>
> I need to generate a field f(x,y) with given variogram. More precisely, I
> have N points (x,y) and I want to assign f(x,y) such that the variable f
> has a spatial autocorrelation structure according to a given variogram
> model.
>
> My impression is that the way to do it is simulat
44 matches
Mail list logo