Questions tagged [spatial-correlation]
The spatial-correlation tag has no usage guidance.
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Help with SAR model interpretation
I am working on a research project that investigates the effect of land subsidence and flood risk on property prices. I have used the Spatial Autoregressive (SAR) model to estimate the direct, ...
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Is it possibe to extrapolate abundance estimates of N-mixture models to unsampled parts of a species range?
I have repeated count data for a part of the range of the species I am interested in, and have used unmarked to get an abundance estimate for these. My understanding is that the population estimate ...
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Performing Chi-Square test (or similar) across a spatial grid
I have a dataframe in R where each row is an sf-formatted geospatial grid. For each grid, I have the number of venomous snakes and the number of non-venomous snakes seen in that area. I also have data ...
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Global and GWR models
I have mortality data for municipalities in my country and I would like to know if an approach such as modelling with a Linear Regression and if the assumptions like normality, equal variance and more ...
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Intersection of matern covariance functions with different parameters
I am trying to prove some ideas about the identifiability of covariance function parameters for small samples. From various numerical experiments, it seems that the graphs of two matern covariance ...
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Contour plots of a patio-temporal covariance function
I would like to plot contour plots of covariance functions in R:
one for a fitted separable spatio-temporal covariance;
one for the empirical covariance function,
similarly to Figure 4.4 in Wikle et ...
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Spatial autocorrelation correction with glmmTMB
I am currently working on a dataset (count data) in which one observation corresponds to one day of monitoring at a site.
The overall protocol is to monitor groups of sites along transects. Almost all ...
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Analysis of spatially correlated count data from a designed agricultural experiment
I have carried out a designed agricultural experiments with two treatments and recorded the effect on the abundance of a pest insect. The field experiment was divided into four blocks with two plots (...
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predict return different values from fitted.value [closed]
I am using lagsarlm in spdep package in r to estimate a spatial Durbin (mixed) model by
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Simulating Space-Time Gaussian data in R with non-separable covariance function
When wanting to simulate Gaussian spatial data in R one can proceed as follows:
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How to mitigate spatially correlated noise in image
I was wondering how can I mitigate spatially correlated noise following power law with filtering or other techniques?
For instance for astrophsics you can simulate it
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What is an appropriate threshold to estimate if there is serial correlation in cross sectional data
I have cross sectional dataset with several groups (46 banks) within the data. I am aware normally one would use cluster robust errors by clustering errors at the group level by including a dummy ...
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How do I account for spatial autocorrelation in my zero inflated negative binomial model?
I am building a zero-inflated NB model, and I know my data are spatially autocorrelated (as per the acf test).
My current model is:
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Spatial Autocorrelation in Fixed Effect Model
I use a two-way fixed effect model (City and Year) to test the relations between local culture and economic growth. I detect spatial autocorrelation in culture (not surprisingly). How would this ...
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Comparing Moran's value between different variables in same geographie
let's suppose I have a dataset with 3 different variables (features) for the same geographie and then calculate the Moran's values for each one. All my variables have a p-values<0.05. Can I compare ...
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Detecting spatial autocorrelation using the proximity matrix from a Random Forest
I was wondering whether one could detect potentially problematic spatial autocorrelation (or other types of data structures) by using the proximity values computed from a Random Forest model?
For ...
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Fitting a well-specified 1D function of time to 3D spatial and spatially correlated data
I have acquired experimental data that can be considered to be a scalar field in physical three-dimensional space, $(x,y,z)$ that I have observed over time, measured on an equally spaced regular grid. ...
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Geoscience Statistical Anomaly - Groundwater Measurements
I am a Geoscientist working in the field taking groundwater measurements every day. I frequently work with groundwater monitoring wells as an integral part of my day. For those of you who do not know ...
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Comparing Mantel statistics
I have the abundance of different species of birds at various locations in a country. From this data I can compute the Bray-Curtis dissimilarity matrix. This question I want to be able to answer from ...
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Decreasing trend in semivariogram of nlme model residuals?
I am new to spatial statistics and am trying to fit some spatial models using the nlme package in R.
I fit three different models, using the same set of predictors ...
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Spatial Error Model vs Conley standard errors
What is the difference (pros and cons) of using an OLS with conley standard errors and a spatial error model? Is there a recommendation for when you should use one over the other?
Thanks!
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Metric to quantify randomness
I have an $L \times L$ matrix representing a $2D$ region. Each entry of this matrix is a real number lying in the closed interval [0,1]. I want to quantify how different is this from a similar $L \...
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Expectation and Variance of Moran's I under the Null
Moran's I is a statistic used to measure spatial autocorrelation. For a set of $N$ spatial units where we get measurements $\mathbf{x} = (x_1, x_2, \cdots, x_N)^T$, and a weight matrix between the ...
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What means that the model is "singular"?
My question might be rather basic, theoretical.
I am running spatial and spatial-temporal bayesian models in INLA. I have areal data and a continuous response variable with spatial and temporal ...
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References on data partitioning (cross-validation, train/val/test set construction) when data are non-IID
Consider a prediction setting in which we are interested in training a regression or classification function $f$ with inputs $X \in \mathbb{R}^k$ and target $Y$, and assessing its expected ...
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INLA model with spatial autocorrelation - binary response, binomial predictor
I have a binary response variable (0/1) and a predictor distributed continuously on 0-1 scale. There is significant spatial autocorrelation in data, thus I am running an INLA model to account for that....
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What are the types of error correlation?
In many fundamental regression models errors are assumed Independent Identically Distributed.
One of violations of this assumption is when the errors are somehow correlated. From what I know it may ...
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