The field of study concerning statistical methods that use space and spatial relationships (such as distance, area, volume, length, height, orientation, centrality and/or other spatial characteristics of data) directly in their mathematical computations.

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Spatial clustering based on response

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 to ...
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6 views

Convert coordinates to neighbor list for spatial analysis in R using INLA [on hold]

I am trying to do an analysis of two greyscale images taken a few seconds apart, where each pixel in the first image should be predictive of the pixel in the second image. In general pixels near each ...
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0answers
14 views

Gaussian Distribution for Latitude/Longitude Coordinates

I have a bunch of latitude/longitude coordinates and if I plot it on a map, it seems to follow a bivariate distribution. I would like to estimate the distribution of points using a bivariate ...
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1answer
46 views

Use of Poisson distribution to analyse distribution of individuals in space

Dytham 2010 suggests using the Poisson distribution to establish whether individuals are evenly distributed in space. Say we end up with a map of individuals in a study site that looks like the ...
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5 views

the relationship betweeen Moran Scatter Plot, LISA Cluster Map and Spatial Lag Model

have read that by means of the Moran Scatter Plot and LISA Cluster Map, pockets of spatial nonstationarity can be indicated. What is exact the spatial nonstationarity? Does it refer to the outlier ...
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11 views

Is using the whole population and sample data as a co-variance in spatial analysis correct?

I have two datasets that I am using to fit a spatial regression model. One is from the whole population (say means of bike usage in each state), and a sample population (statistics means of those with ...
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6 views

Quantifying spatial-temporal variation

Imagine a set of territories each subdivided into 5m grid cells. Each grid cell represents a spatial unit, and that unit can have any number of variables associated with it - e.g. habitat ...
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1answer
39 views

How Does Kriging Interpolation work?

I am working on a problem in which I need to use Kriging to predict the value of some variables based on some surrounding variables. I want to implement its code by myself. So, I've went through too ...
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2answers
29 views

Finding cluster number based on distance & max element count

Given two constraints: The maximum distance d an element can lie from a cluster centroid (or medoid) The maximum number of elements n in one cluster Is it possible to find the minimum number of ...
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17 views

Compare Procrustes values

I have two sets of spatial data which underwent a transformation. I'd like to compare the effect of the transformation on two sets of data to test the hypothesis that the transformation had a larger ...
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31 views

Estimating a dynamic spatial panel

I am analyzing a spatial panel dataset using the XSMLE package in Stata. My units are a subset of US states (11) and my panel is strongly balanced. The package returns estimations for Main, Spatial, ...
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10 views

Modify dot product for dimension independence

The distribution of the pair-wise dot products of uniformly distributed points on the unit sphere depends upon the dimension n (see, e.g. here). What alternative similarity measures exist that do not ...
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43 views

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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17 views

Contingency testing in geographic data with the issue of independence?

How can I test contingency between two variables in geographic data with the issue of independence? I have a column of fire frequency and a column of vegetation change but do not think a simple chi ...
3
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1answer
63 views

Spatial autoregressive model implementation in R [closed]

I need to implement a SAR model with no covariates. To be more specific, the regression I have to estimate is y=bWy+e where: y is the dependent variable; b is the coefficient parameter to be ...
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0answers
8 views

Is it possible to extend dynamic spatial (space-time) panel model to a SARAR (SAC) specification?

I have panel data of 200 regions over 20 years. My goal is to estimate a dynamic spatial (space-time) panel model. I would like to employ an extension of model used in Debarsy/Ertur/LeSage (2009): ...
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3answers
70 views

Any easy way to cluster GPS trajectories?

Can anyone recommend an easy way to cluster hundreds of GPS trajectories to find out their common paths? The GPS data is coming from different vehicles that have traveled thousands of miles.
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30 views

Test whether cross-sectional dependence in panel data follows known (network/spatial) structure

I want to test whether cross-sectional dependence in one specific variable (y) in panel data format follows a known structure (W) (e.g. network, spatial dependence), after controlling for individual ...
2
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1answer
27 views

Estimating a peer effects model in R

I would like to estimate a model of the following form: $$ y = \sigma G y + \beta X + \delta G^* X + \epsilon $$ where $G$ and $G^*$ are quadratic adjacency matrices, $y$ is a vector of a dependent ...
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1answer
32 views

Homogeneous vs. Inhomogeneous Poisson point process

What are the main theorical differences between the homogeneous and inhomogeneous Poisson point process? What are the aspects and condition of my data that I can determine which point process best ...
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0answers
8 views

Spatial regression-one explanatory variable is determined by other explanatory variables

I am doing a spatial analysis of the relationship between nutrient loss, intensive inputs and farm characteristics. However, the dairy yield is also determined by intensive inputs; also, dairy yield ...
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0answers
34 views

How do I interpret lagsarlm output from R's spdep?

I've run lagsarlm on my dataset, using a mixed model and using a row-standardized adjacency matrix. I have results that I think are good, but would am not sure how ...
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0answers
6 views

Use of mantel test to test spatial correlation between single and mixed-species groups

I am trying to see if there is spatial correlation between species found in single and mixed-species sightings using location-specific data. I used a mantel test (geographic distance, Euclidean) in ...
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0answers
14 views

Calculating leverage/cook's distance for a Weighted Spatial Simultaneous Autoregression Model

I am estimating a Weighted Spatial Simultaneous Autoregression Model (spdep::spautolm --> Link) in R and I would like to do some residual analysis. Unfortunately ...
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1answer
31 views

Computing Issues with Kriging

I am having some issues with Kriging in R, and I was looking for some idea where I am going wrong. From what I can tell, I done a decent job removing the trend, and I believe my transformed data is ...
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33 views

How can I compute multicollinearity (VIF) in R, and know if it's safe?

I am working on a group project for a university course on "big data research methods". My data is aggregated by neighborhoods in Chicago. My dependent variable $Y$ is the property crime rate (per ...
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29 views

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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22 views

How to compare Pearson correlation coefficients from spatial data [duplicate]

Dear "Cross Validated" community, First I want to introduce my data to you, so that you can get a clear overview regarding the problem I´m confronted with. For some urban studies I´ve got a spatial ...
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16 views

Correlating aggregated values between groups

I am currently analysing data from household surveys in 27 Indian villages in 7 states, with about 30 cases in each village (807 in total). The aim is to find relationships between various factors and ...
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1answer
17 views

Is spatial eigenfunction analysis a kind of direct gradient analysis?

Everything is in the title. By eigenfunction analysis, I mean using methods based on Moran's and asymmetrical eigenvector maps. I have a trouble to understand if they overlap or if one is just a ...
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36 views

Help with R packages to use in my spatial discrete choice model

I am at a loss as to which R package and approach to use for my modeling. The background is: I have a transportation cross-sectional survey dataset combined with many other GIS datasets. I am ...
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1answer
48 views

Condensing spatial time series data and spatial interpolation

I have spatio-temporal albedo (roughly, the 'reflectivity' of earth's surface) dataset, from NASA's MODIS satellite, for a 130 square kilometer area. The dataset contains raster files in the NetCDF ...
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0answers
48 views

Is there any difference between spatial correlation and spatial autocorrelation?

What is spatial correlation? Is it the same with spatial auto-correlation or it is different?
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32 views

Is it meaningful to compute a radial kernel density estimate from 2D data?

I am working with 2D spatial data, $(X_i, Y_i),\; i=1, \cdots, N$. My current research requires estimating the density of the distances between those data points in each of the two dimensions. So ...
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1answer
40 views

MAUP: correlation increases with aggregation, would error decrease?

I know that, due to MAUP, as you coarsen the scale of analysis, you can expect the correlation coefficient to increase, variance to decrease (?), and regression coefficients to fluctuate. Is there ...
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53 views

What is the theory behind using eigenvectors for spatial filtering

As a programmer I have used the spdep package successfully for spatial filtering. But would appreciate it if someone could offer a description (preferably with supporting references) of how this ...
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1answer
116 views

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. ...
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0answers
29 views

Geostatistics: disaggregating regional data to subregions

I have been reading a lot on geostatistics. I am still unsure this problem falls under the umbrella of geostatistics, or if it is statistically feasible at all. I have the market share for a company ...
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34 views

Incorporating systematic error in (spatial) predictive modelling

I have created a model (random forest) and withheld 20%. When I apply the model to the withheld dataset and check the residuals against the real values I can see there is a systematic error e.g lower ...
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1answer
50 views

Mantel test and Moran I giving different result for same data sample

I want to check spatial correlation for my data about fecal coliform values in water measured at different location. For this I have tried both Moran.I and the Mantel test. They are giving different ...
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35 views

Does negative binomial regression assume sample independence?

I'm working with a negative binomial multiple regression and I'm wondering about the assumption of spatial independence of samples. White and Bennetts (1996) say that the assumption of spatial ...
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0answers
46 views

Interpretation of scaled data in a logistic regression analysis

I have a variable (distance to road; measurement=meters; see below) that contains a right-skew and percentage data (0-100% based on amount of habitat in a moving window; see example below) in a ...
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0answers
107 views

Manual two-way demeaning panel data in R

I'm trying to manually demean panel data by both time demeaning and cross-sectional demeaning, yet haven't been able to do it well. The best thing I can think of is looping through the means for each ...
2
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0answers
11 views

How do I demonstrate threshold proximity between the movement of one object on another?

I'm hoping you can advise on what may be a very simple problem. Here's the scenario: I have several maps of an estuary, each separated by ten years from the last. On each map are two variables: ...
4
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1answer
290 views

Feasibility of Negative Binomial Spatial Regression

I have a set of crime count data where it appears that the data take on a negative binomial distribution. I have had some success converting the dependent variable (a crime count) into a rate and then ...
0
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1answer
41 views

What to make of countervailing spatial regression coefficients?

I am running regressions across a country's counties (N about 300). I divide the country in two regions A and B to control for potential unobservables. My explanatory variable varies at the county ...
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0answers
57 views

how to bootstrap data on irregular grid?

I have irregular gridded data and I wish to resample from this data in such a way that the spatial correlation in the data is preserved. I will assume that grids that are within 300Kms of one another ...
0
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1answer
21 views

Learning a spatial function

I have some observations of a variable y, that varies spatially. For each observation, I also have a lat, long tuple. I have some 50 or so observations. Besides conducting some exploratory analysis ...
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33 views

Testing whether neighbors are more similar to each other than distant points

Suppose you have points x1...xn in a metric space X, each is associated with some measurement y1...yn. I want to test whether points closer to each other in X have similar associated value y. I have ...
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51 views

Difference between spatially autocorrelated logit methods

I am seeking advice on different methods to account for spatial autocorrelation in logit models. I've seen a lot of different models attempt to address all of the issues with spatial logit models ...