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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Multivariate dichotomous variables against continuous data

I'm trying to establish the relationship, if any, between a series of dichotomous independent variables, and a continuous variable. The data in question relates to the spatial statistics (continuous ...
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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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11 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
13 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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19 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
27 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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11 views

R - Combining and visualising spatial data [migrated]

I'm trying to combine some spatial data with a csv data frame then produce a visualisation of some features of the result using ggplot2. When I combine the data and then try to fortify the result so ...
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37 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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22 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
35 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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40 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
93 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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23 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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27 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
25 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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27 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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31 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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66 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 ...
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10 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: ...
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1answer
179 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 ...
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1answer
38 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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38 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 ...
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1answer
19 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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30 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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24 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 ...
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44 views

Calculate prediction interval for SAR model (errorsarlm function in R)

I would like to predict prediction interval for a SAR model (function errorsarlm in R - package spdep). While the function predict.lm allows to set interval='prediction' parameter to predict the upper ...
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18 views

Testing causes of accident blackspots on road network

Say I have a way of predicting, for each link on a network, the likelihood of road accidents. I also have a (mercifully quite sparse) point data set of recorded accidents. Bearing in mind that the ...
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37 views

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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47 views

How can I evaluate spatial autocorrelation in a binomial GLMM?

Following Dormann et al 2007 Ecography, I have employed a GLMM approach in R to account for spatial autocorrelation in a binomial regression model (logistic regression) that does not have random ...
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1answer
62 views

Is it valid to use a model-variogram fit not on the full range of lag distance?

I am trying to implement a form of 2 stage least squares, in step 1 I ignored the spatial correlation between the observations, now in step 2 I look at the spatial correlation of the residuals of step ...
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1answer
121 views

Intrinsic spatial stationarity: doesn't it only apply for small lags?

From the definition of Intrinsic stationarity: $E[Z(x)-Z(x-h)] = 0$ This assumption is used for example in ordinary kriging, instead of assuming a constant mean over the entire space, we assume the ...
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9 views

Classification for series of lat, lon points of varying lengths

I have a dataset of series of latitude and longitude points. Each series of points corresponds to some activity. The number of latitude/longitude points is not the same for the series. My dataset ...
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31 views

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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1answer
38 views

How to use geometric proximity in classification

I am doing a classification of certain regions of an image. Let's say I have done the classification, and some classes have been classified positively (negatively) with high probability. For my ...
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1answer
101 views

Correcting for spatial autocorrelation in dissimilarity datasets

I have a community assembly dataset with 299 species at 15 sites. Im interested in correcting for the effect of spatial autocorrelation on beta-diversity (or species turnover). Dataset here. There is ...
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16 views

Multiple Imputation for Spatial Models

I'm trying to estimate various spatial models (SAR, SDM, SEM) but have missing data throughout my variables. The mice package in R gives a straightforward solution when none of the variables with a ...
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2answers
41 views

Direct parametrization of Cholesky decomposition of spatial covariance matrix

In spatial data analysis, a simple way to model the covariance stucture between spatial observations is via a covariance function like $cov(y_i,y_j) = C e^{-rD_{ij}}$, based on some (euclidean) ...
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1answer
50 views

PDF of Distance between the centre of a regular hexagon of radius R and any point within it

What is the probability distribution function of the distnace between the centre of a regular hexagon of radius R and any point within it? I have done the following and would appreciate if you could ...
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1answer
71 views

Spatial coordinates (latitude and longitude) are non significant

I want to use latitude and longitude as a feature for models like SVM or Logistic Regression (both for classification). What is the most common approach to use latitude and longitude values as ...
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0answers
28 views

Is there a minimum sample size for Besag's transformation of Ripley's K-function?

I am using Besag's L function to test complete spatial randomness for plant populations. Specifically, I am implementing the univariate L-function Lest in R on a ...
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1answer
234 views

Spatial Cross-correlation Function

I have code that calculates a bias-adjusted estimator xi(r) defined as a measure of the excess probability dP, above what is expected for an unclustered random ...
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0answers
28 views

Y vs X with spatial variation

I am trying to learn a relationship between two variables Y and X, X is the independent variable. The nature of the relationship is quadratic, from some domain experience, but the relationship itself ...
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15 views

Partitioning Spatial Dependence?

So, I have a group of nations that exhibit global spatial dependence. I want to partition the nations into groups so that, at an intuitive level at least, the "sum of the spatial dependence within ...
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0answers
44 views

Determine size of quadrat by point pattern analysis

I'm working with a considerably large spatial point dataset that is irregularly spaced. As I want to average the data based on a particular quadrat size (essentially square grids) I was wondering if ...
3
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0answers
47 views

Goodness of fit for a spatial panel with fixed effects and both spatial lag and spatial error

On a dataset, I performed spatial panel regressions with fixed effects, and with both a spatial lag and a spatial error (both are significant), using package splm in R (Millo and Piras 2012 Journal of ...
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65 views

Should I check the z-score if the p-value of Local Moran's I is significant?

The dataset I'm using contains income data per area. The values are not normally distributed as shown in the following diagram. Global Moran's I indicates significant spatial patterns and Local ...
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14 views

Conditional Distribution of an Independent Variable for missing data

Let $X=[X_1 X_2 X_3 ... X_p] $be a matrix of p independent variables where $X_i=[x_{i1} ... x_{in}]'$ is a nx1 vector. Let W be a nxn weight matrix based upon queen contiguity (so zero's along the ...
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1answer
38 views

How to determine if there is a spatial dependence in data?

My data consists of data measured at different positions (250 measurements in a 5x5 grid). It has been proposed that results may be somewhat dependent on the position. Looking at the data I don't ...
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1answer
76 views

Residuals plot from ripley K function on spatstat

I am a rookie on R and on spatstat package. I would like some help with the Kres function on spatstat. As is always wise to plot the residuals from any kind of ...
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1answer
49 views

Bayesian models vs Bayesian network models

I'm new to statistical modeling and working on applications in spatial property prediction. Can you help me understand the difference between a hierarchical bayesian model and a bayesian network ...