# Questions tagged [geostatistics]

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

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### EM-algorithm for spatial data

I am very new to Geostatistics (Modeling spatial data) and have some questions: 1- I found that in many literature, the spatial random field is divided into spatial bins. That is, suppose I am ...
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### Enforcing symmetries "for bag-of-vector" data in XGBoost or random forest - geodata example for illustration

I'll give a concrete toy problem, then give some comments on what sorts of abstractions I care about. Toy problem: Each person $i$ in my dataset has a phone, and every once in a while the phone will ...
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### GAM model with spatial account via MRF

I am starting to read a little about generalized additive models and how spatial dependencies can be incorporated into the model, I'm reading Generalized Additive Models An Introduction with R from ...
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### Imputing missing observations of zip code level data

I am looking for a sufficient imputation method for missing observations in my zip code level data, using R. I have a random sample consisting of households which live in different zip codes within ...
1 vote
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### Can we apply geostatistics on data which is not normally distributed?

If we work on groundwater data, if the data is not normally distributed, can we apply geostatistics on this data without transforming it to normal distribution?
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### Statistical Integration of Bayesian and Frequentist Approaches: Weighing Methodology

I'm uncertain about where to post this question. I'm currently working with geotechnical data (soil parameters) and aiming to obtain realistic and safer parameter values. To achieve this goal, I've ...
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1 vote
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### Statistical test whether data conforms to a spatial point process--gaza bombing locations

I came across this image on twitter, and it made me think about testing a point process hypothesis. Now this is a politically sensitive image, and I don't want to run afoul of any SE posting ...
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### Compare and aggregate indicators at different geographic scale

I encountered a problem in developing an aggregation model of several indicators. Almost all the indicators are at a small geographical scale (admin2 / Provinces), but one is at larger geographical ...
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### Larger vs smaller areas for analysis: how to make a choice?

I am researching the composition of labour force, and my variable of interest is the share of workers in a specific occupational category. I measure it by parish and also measure a set of explanatory ...
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### How to model user behavior with a time series of discrete locations in continuous time?

I have a dataset that contains the sequential locations a user has visited, with start and end times. A small sample: ...
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### Geostatistics: Covariance vs Semivariance

I am confused by the following page in Geostatistics for Environmental Scientists, Webster & Oliver: My understanding Given locations specified by a vector $\mathbf{x}$, we assume an underlying ...
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### Spatial analysis: How to find region most prone to storm loss when only have loss data for whole region?

I'm thinking about a statistical problem and I would be grateful if you could give me some hints of how I could address this problem: I have data of n insurance companies and for each insurance ...
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### Covariance estimation in simple kriging: the "dead end" problem (authorization of using variogram)

I am confused about the presentation of using variogram in simple kriging in the book of Multivariate geostatistics by H. Wackernagel (1995). I understand the process of derivation of simple kriging ...
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### Declustering spatial data and kriging

I am doing a simple project on a mining dataset and came across some problems: Should I use the declustered values to model the variogram? Do I apply ordinary kriging to the original or to the ...
1 vote
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