Questions tagged [geostatistics]

Statistical modeling and analysis of georeferenced data, often modeling spatial covariance. An example is kriging.

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How to impose spatial continuity constraint onto clustering?

Statistics version: I have a few measurements of a function that takes three inputs and produces a few 2D fields of outputs: $f(a,b,c;x,y)$, with $f$ being a vector of several quantities. I would like ...
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CAR spatial models in JAGS

WinBUGS comes with the GeoBUGS add-on, which contains a number of predefined model structures that are suitable for modelling spatial data structures e.g. geostatical structures (spatial.exp), ...
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cokriging and generalised linear spatial models

The answer to this question gave me an interesting idea. The part that interested me was a brief description of kriging concluded by The way, kriging as usually practiced is not quite the same as ...
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Interpretation of probability in geostatistics

In geostatistics, the concept of a random field is used in e.g. Kriging. Hence, at each point in your study area, there is a probability distribution. Should this probability be given a frequentistic ...
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Car out of route

I have one KML file that describes the movement of a car. Data comes from sensor in the car, contains wrong or noisy measurements. I want to filter the wrong measurements, i.e. throw away the ...
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Which methodology/algorithm can be used to complete this 'fill in the blanks' problem?

I have 'n' realization of some phenomenon (historical observations). From the image below, blue cells represent observing a specific event and the white cells represent not observing the event. The ...
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Cokriging variances differ using cross validation

I'm investigating cokriging using various metals in the Meuse dataset but the variances output by R when I predict values at gridded points differ substantially from the variances produced by cross ...
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Correlating Two Time Series with Gaps in Data and of Different Lengths

I am attempting to correlate the time series from 4 separate tilt monitors that sample every 5 minutes. The time series have slightly different base times and end times, and the resulting arrays are ...
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Using Markov random field spatial weights to account for spatial autocorrelation

I am looking at the relationship between life expectancy and smoking rate within the London boroughs. I thus created a bayesx spatial regression model including a term which assigns spatial ...
85 views

Anomaly detection with geo spatial data

I have geo spatial data. Dataset represents concentration of something. For instance, social media activity of people in point [time, lat, lon] I have some list of feature for every points (lat, lon):...
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Integrating logistic regression with CA to simulate land cover after prediction

I have used logistic regression in R to predict the probability of change in 3 types of land cover, the map of probability is generated for my case study. I do not know how to use the probability ...
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Which is the best model for explaining spatial distance between points?

I have a dataset with distances between beneficiaries and the nearest provision point (nearest hub). I want to develop a model to explain distances based on several atrributes like category of ...
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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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Controlling for spatial confounding in point-referenced data

I have a point-referenced data set with 2 binary outcomes. The data shows a strong correlation between these binary attributes - however, the geographic clustering is also qualitatively clear. I would ...
143 views

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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Cerioli's modified test of indepence with spatial data

I have to two datasets $X$ and $Y$ with binary observations on a regular grid. A regular contingency test for independence would be flawed by the presence of spatial autocorrelation. Cerioli (1997) ...
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How much data do I need in spatial hotspot analysis?

I'm now doing a project about spatial hotspot analysis. I read many literatures, however, I can't find any papers tell how they determine the data size they used. I mean, suppose we have crime ...
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What is 5th order kriging?

For our foray into geostatistics we got data that consists of measurements taken from the soil. The dataset has like concentrations of various different minerals. We were divided into a number of ...
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type of continuity in geo-statistics

I am reading the book by Wackernagel, H. (1995) Multivariate Geostatistics: An Introduction with Applications and on page 49 The fit is done by eye because it is generally not so relevant how well the ...
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Clustering/pairing users based on multiple lat/lon values?

I have a data set that contains entities and lat/lon values for each one, potentially multiple lat/lon values. I believe that some of these entities may actually be the same person, although I can't ...
215 views

Predictive model with geospatial data

I have datas of random events with gps and time variables. I would like to compute probabilities of an event happening at a given time and location. In the training set, we have about 1500 possibles ...
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How to objectively decide when the value is stable?

Let's say that I've build models using three different values of some parameter (for example Max Tree Depth) in 1500 iterations. Right now, I want to decide after how many iterations the accuracy ...
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Improve rate estimates of geo. events by other attributes?

I have somewhat rare events (at given times) at geographical locations. I also have a lot of static data about each micro-region. Some of the static data is likely to be correlated with the true event ...
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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, ...
119 views

Variance and Variograms: Sigma?

Can someone please walk me through this morass of Ļ's? There is a sigmasq in the summary output from geoR's likfit. Really this is the one I'd like to know about. I'm not clear which of all of the ...
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Details on kriging and variograms

I was wondering what are the steps to perform factoring kriging. I know it is used to extract specific components that may have a physical meaning and this is achieved by kriging. However, I have some ...
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How do you constrain variogram estimates to be a percentage?

I am interpolating soil texture data with GeoR and ARCGIS. The ordinary kriging process is straight forward and GeoR facilitates cross validation. Has anyone else produced variogram parameters, nugget ...
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geographic distance and mahalanobis distance

I am trying to match individuals based on monthly consumption and geographic consumption in a dense metro area. Essentially I want to create treatment and control pairs with the having both geo ...
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How to calculate the significance of change between values in the frame of an equal territory over time?

I do not know much about statistics as you could notice below. I need to calculate the significance of change in land cover in two periods of time. The problem is I have two equal by surface ...
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Gradient map based on probability of incident

I have a binary classification model that outputs the probability of an instance belonging to the positive or negative class. I already have the probability threshold by which an instance will be ...
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Smoothing methods for geographically aggregated data?

I have some Canadian census data with various statistics defined by dissemination block. These blocks are irregular in shape since their boundaries are based on the road network. I thought it would be ...
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How to predict the time of next trajectory for users

I am working with the Geolife dataset and would like to create a statistical model to predict when users will go on their next trip. The implication is to see if we can build a model to be able to ...
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Statistical analysis of polygons QGIS : find areas of statistical difference

I have polygons for the country divided into E.D. areas. These polygons illustrate the average annual rainfall in their ED area. Is there any way to statistically tell if one polygon area has a ...
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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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Do I need a special kind of linear regression for aggregated data?

I have two separate databases on individuals. But these individuals are not both present in the two databases. So I decided to aggregate them into area-level data (such as State-level). One of the ...
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Why likelihood based geostatistical modelling slower than non likelihood based counterpart

Likelihood based geo-statistics (geoR etc.) are usually slower than non-likelihood based geo-statistics (i.e. those based on just least square fitting, for example <...
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How to implement Kriging without x and y coordinates

I have some sample measurements taken from different locations. I want to predict the measurements in some surrounding locations that were not studies, for this I want to use Kriging. However, My ...