Questions tagged [variogram]

A plot or function used in spatial statistics (or in time series analysis) to describe the degree of spatial (or time) dependence of a stochastic process.

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What am I not understanding about semivariogram and Normal Score Transformation?

I have generated this two dimensional random field: This is done following this page. In particular, I have selected t=23 as dataframe and I have changed some parameters. As you can noticed, I have ...
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Generate a syntetic log-normal two dimensional random field

I would like to test some functions that I wrote related to the kriging applied to rain data. In order to do that, I would like to generate a synthetic log-normal 2D random field. The idea is to ...
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Empirical bayes estimation of variograms for multiple variables

I am looking to estimate variograms, or spatial correlation matrices on all columns of a data matrix $\mathbf{X}_{n\times p}$ with $p>n$. The matrix of spatial coordinates $\mathbf{Y}_{n\times 2}$ ...
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Residual autocorrelation in non-stationary (gaulss) model

I'm fitting a non-stationary model using mgcv (family: gaulss()) where the data have been collected at different points in space....
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How do you express the variogram $\gamma(u)$ in terms of correlation for a stationary process?

The Analysis of Longitudinal Data textbook by Diggle et al. (2002) mentioned twice (p48 f. and then on p82) that given the following definition of the variogram, \begin{equation} \gamma(u) = \frac{1}...
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No convergence when fitting theoretical semivariogram to empirical?

I'm kind of new to working with semivariograms. But I just wanted to fit a semivariogramm to my data and when fitting the theoretical variogram to my empirical it tells me that: ...
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Interpreting a Distance & Time 3D Variogram for Variogram modeling

I am trying to understand some concepts of variograms. I have made several variogram models in R and am trying to understand exactly what they mean. My data is ...
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Variogram fit in R not converging

I have taken a shapefile from Open NYC Data and performed the following method. My end goal is to predict Taxi trip_duration at various points across the city of ...
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Variogram of categorial data?

I have a thematic map as raster data with classes assigned as numbers: 1,2,3,4. These are categorial classes and have no linear meaning. I am interested if there is spatial autocorrelation in this ...
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Semivariance: Are these two formulas equivalent?

Mean Semivariance optimization defines semivariance, variance only below the benchmark/required rate of return, as: $$\frac 1 T \sum_{t=1}^T [\min(R_{it}-B,0)]^2$$ where $B$ is the benchmark rate, $...
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Why do you need a variogram for Kriging? goldingn/gpe package?

I am using golingn/gpe (github) package, and it does not provide a variogram and instead look at co-variances. Is it possible to do kriging without providing variograms?
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why variogram models take only one independent variable

lznr.vgm = variogram(log(zinc)~sqrt(dist), meuse) i am using meuse data for practicing to create variogram models, but i am confused to know there are 14 ...
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Should a nugget ever shift the variogram away from zero at distance zero?

I had frequently seen the definition for a "rigorous" spatial isotropic semivariogram being defined as: $$ \gamma(h) = K(0) - K(h) $$ Where $K$ is a positive definite covariance matrix. If the ...
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Problems fitting a model to a variogram

I am having problems fitting a variogram model. I tried to change some parameters to estimate or fix them but I am still not achieving any improvement. I remove trend of the data and use logarithms ...
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Cokriging, zero distance semivariance [gstat]

Trying cokriging with simulated data, I faced a problem that did not seem one in the demo(cokriging) with the meuse dataset: I can't use ...
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How to interpret semivariogram parameters from two different raster images?

I know the definitions of the components of a semivariogram. However, I would want to know how they could be interpreted when applied to actual scenarios. For instance, I have two EVI (enhanced ...
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How can I understand these variograms?

Using grf function from R package geoR, I simulated 6 replicates (each with 1000 samples) of a Gaussian random field on ...
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Mixed model with serial correlation and random slope?

I'm making a mixed model for some longitudinal data, where the response is measured fro multiple individuals over time. I have made a model with random intercept, random slope and gaussian serial ...
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What is the nugget effect?

I don't understand exactly what is meant by the term "nugget effect" in geostatistics. When looking at empirical variograms plotting the variogram $\gamma(h)$ vs. the lag $h$, the nugget is defined as ...
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Temporal Variogram

Can we compute temporal variograms just like spatial variograms? I know about spatio-temporal variograms but I am more interested in doing a comparison of separate spatial and temporal variograms and ...
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How do you interpret this variogram?

Description: 8000 spatial data points spanned over an entire state 200 bins are used My question: Is the variogram telling something about the nature of the data? Why is it fluctuating? Should I do ...
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Spherical vs. Exponential Kriging Covariance Functions

A statistical epidemiologist colleague of mine told me that in comparing spherical vs exponential kriging covariance functions, only the latter (i.e., exponential) function is generally a valid model. ...
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How SHOULD a variogram plot look like?

Say you fit a model m. You then calculate the variogram. In R, this can e.g. be done by using plot.Variogram using the nlme package on an lme object. Say the plot indicates that yes, there is some ...
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Explain Like I'm Five version for Variograms in R's gstat package

Long story short, I asked a question on StackOverflow about Variograms in the gstat package in R. The person who answered gave me some tips on creating the variogram using the package. My dataset is ...
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warning when fitting variogram - gstat

I'm trying to build a variogram model of the semi variance in Zn concentration with distance using gstat package in R. First I plot the variogram based on my data (it clearly seems to mean that the ...
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Variogram to constrain kernel density bandwidth

I have linear structures transformed into points and spatially distributed like this: I want to perform a kernel density so that zones with lots of structures present high density. The problem is ...
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How much difference in the Akaike Information Criterion is reasonable between a Spatial and a Non spatial Model

I am doing supervised land value modelling (900 observations) and I am comparing two approaches to do a variable selection (51 variables). I am using R. The first one is a backward step-wise ...
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Why is positive definiteness necessary for kriging?

I understand from wikipedia that a variogram model must be positive definite to be used for kriging: Note that the experimental variogram is an empirical ...
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Is there a way to find optimal sensor node locations in a domain when all data is known?

I have an x-y domain where I know the snow depth everywhere. (i.e. the granularity of the values is such that I can assume I know it everywhere). I want to use this information to inform where to ...
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I am not sure if my data are spatially autocorrelated or not.

I have been trying to figure out if my data are spatially autocorrelated by generating semivariogram of the residuals. I do not get the shape similar to any variogram (spherical, exponential or ...
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What is the computational complexity of the empirical variogram?

If we use the method of moments estimator: $2\hat{\gamma}(h) = \frac{1}{| N(h) |} \sum_{N(h)} (Z(s_i) - Z(s_j))^2$ What is the computational complexity? My initial assumption was that it would be $...
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Is there an approach to combining variograms?

If we compute two seperate variograms for the same type of measurement, but the areas which they cover overlap, is there a logical way (or does it even make sense) to combine the two variograms? ...
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Why is my semivariance so high?

I am using variograms checking for spatial autocorrelation in a resiudal pattern produced by a GLMM-NB. In theory, the semivariance should be bounded between 0 and 1 (that´s what I think at least as I ...
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What does it mean that a variogram keeps increasing with distance?

I am modeling my 3D dataset with a Gaussian Process with square-exponential covariance. To test whether this is a good model, I subtract the mean from the observed data and then calculate the ...
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Kriging: fit.method and dX argument in variogram

I would like to krige residuals (from multiple linear regression) of yearly precipitation totals from a 50 years time series. Every year has been regressed individually. The residuals will be added to ...
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Interpreting Spatio-Temporal Variograms

I've got spatio-temporal disease data at the county/annual level for 2000-2014. I'm analyzing it to try to pull out temporal variations in disease incidence and was told that I should generate a ...
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Variogram with custom distance matrix

I work in marine ecology and as such all of my distance matrices are constructed using the shortest possible marine route - i.e. avoiding any land. Here is a plot of my "marine distances" against "as ...
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Critical scale of variation of tree biomass using variography

I have a combination of a philosophical and a technical question. I am interested in an application where I am trying to find a critical scale of autocorrelation of tree biomass on the landscape. Let’...
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Gstat: Modelled semivariogram values not matching plotted model using the variogramLine function

I am trying to extract the semivariance values associated with a given semivariogram model developed in gstat, the end goal being to compare modelled semivariance with observed semivariance at defined ...
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Gaussian Mixture Model: bandwidth parameter versus variogram fitting?

I'm estimating a stationary, spatially random variable over a 2-dimensional domain. I have ground-truth measurements in several locations, over time. I need some way of spatially-interpolating ...
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Simple Kriging with linear semivariogram

While studying how to develop a simple kriging model with a linear semivariogram, the various tutorials point towards creating a covariogram using $\sigma(h) = \sigma(0) - \gamma(h)$, but the value of ...
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Non-parametric variogram estimators

I'm working with overdispersed, count spatial data. The goal is to look specifically at spatial dependence patterns. I'm trying to fit variogram models to empirical variograms, however the only ...
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Lag lengths are larger than my domain in gstat in R? variogram object

My problem is that the my resulting variograms are of a larger lag length than my domain. I have the following code to compute lags in the vertical direction: ...
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Fitting a variogram model with the pairwise distance matrix supplied

I'm trying to fit a variogram to my data, however the spatial points are confined by an irregular polygon. So I'd like to supply a variogram model function with the distance matrix of the points. I'...
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Measurament error from semivariogram

I am looking at a model to determine the measurement error for a set of measurements of a spatially correlated phenomenon (sea surface temperature measurements) using a semivariogram technique. For ...
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Universal kriging: which variogram to use?

I am working with the build in dataset meuse, which has 155 measurements of Zinc and the distance to the river "Meuse".(http://rspatial.r-forge.r-project.org/gallery/). Now I am trying to imitate ...
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Kriging results are too localized, how can I increase the influence of each data point

I have a small dataset that looks like this... ...
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AIC or similar selection techniques for Variograms?

I have a very basic question: how does one choose the "best" variogram? It is possible to fit different models to an empirical variogram, e.g. nugget, ...
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R Error in chol.default(A) krigeST from gstat package

I am working with an hourly dataset of air temperature, recorded at ~200 stations over a relatively small area. I chose a space-time variogram (e.g. sum-metric) to fit my data and am now trying to ...
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Weights in the fit.variogram method of gstat

I'd like to know if I understood correctly the following. In the fit.variogram method of the gstat library, there is a fit.method...
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