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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use “spml” for unbalanced panel data?

I wonder if I can use R's "spml" package for unbalanced panel data. Millo's paper and example are all based on balanced panel data. I try to apply it to an unbalanced panel data set, but got the ...
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19 views

Spatial Autoregressive Poisson model in R

I am estimating a gravity model of migration on cross-sectional data. The Moran I statistic indicates a positive and significant spatial autocorrelation in the residuals of the non-spatial model, and ...
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How do I link two-digit Dutch postcodes to latitude and longitude for mapping data to a map of the Netherlands? [migrated]

I want to show data on a map of the Netherlands. To ensure my Dutch participants' privacy, I only asked them to specify the first two numbers of their postcode. I found latitude and longitude for all ...
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13 views

Pseudoreplication in regression meta-analysis

My understanding of spatial correlation in regression analyses is that the results are statistically invalid; however, I repeatedly see studies published in high-level academic journals that give no ...
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46 views

R: finding spatial patterns in rasters (Moran's I etc)

i'm not really experienced in spatial stats yet, but i'm growing into it. I basically want to ascertain if certain values in a raster are a) autocorrelated and b) are more likely to exist in a ...
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14 views

How to interpret Interactions in a spatial fixed effect model

My units of analysis are racial groups nested in Metropolitan Areas, such that I have an observation for each racial group that is present in a Metropolitan Area. I include a fixed effect for the ...
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31 views

Arbitrary spatial autocorrelation

A spatial autoregressive model includes a spatial lag of the dependent variable. $$ y = \rho W y + x\beta$$ Where $W$ describes the spatial relationship between elements of the model. I have heard ...
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1answer
50 views

How to test for spatial correlation in my data

I am new to the realm of spatial statistics, so I need some help. I have data that locates foreign-owned firms by XY coordinate and domestically-owned firms by XY coordinate. I have plotted the ...
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6 views

Spatial sample coverage and spatial autocorrelation influence on random field evaluation

Ok, I am required to tackle a very though problem with very limited knowledge of even basic statistics. Basically I need to study the following: 1) I have a quantity randomly distributed over a 2D ...
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8 views

Multiple Spatial Dependence Weighting Matrices

Is it possible to use multiple weighting matrices in spatial error models? A possible use case might be when there are more than one way that areas could be related. For instance, states in the U.S. ...
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8 views

Interpretation of Mantel r correlations

I am using mantel in R package Ecodist to perform a series of partial mantel tests. I am examining the correlation between a species composition (Bray-curtis ...
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21 views

Adjusting for spatial autocorrelation

I have a data set on sand martin population sizes along a stretch of river over 40 years. The river is split into sections and the number of birds per section was counted. I have been trying to ...
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12 views

Compact Spatial Clustering with exogen variable

I have a table with 2400 polygons being a partition of a country at a low level. I have as well the population and the area for each polygon, giving me the density of each polygon. I would like to ...
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41 views

Is there such thing called a Uniform point process? (not Poisson point process)

We know a Poisson spatial point process is characterized by the following properties: The Total number of points N follows a Poisson distribution Given N, the point process is a uniform distribution ...
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1answer
51 views

Measuring spatial correlation using a distance-decay model

I asked a question on the GIS StackExchange site, regarding working spatial correlation/regression in QGIS, and how to implement this in software: Calculating spatial correlation between features from ...
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31 views

Violation of 1) normality of error terms, 2) heteroscedasticity and 3) spatially correlated error terms.Alternatives?

I am using linear (Ordinary Least Squares) regression to estimate the coefficients and model fitness for vegetation in an ecological study. However, after model fit, tests showed that the linear ...
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1answer
42 views

Interpreting the value of pair correlation function

I'm attempting to learn various methods for summarizing spatial statistics, and I'm struggling to understand how to interpret the value of the pair correlation function. This link gives a nice ...
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20 views

Variogram with custom distance matrix

I work in marine ecology and as such all of my distance matrices are constructed using the shortest possible marine route - i.e. avoiding any land. Here is a plot of my "marine distances" against "as ...
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16 views

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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52 views

Fit linear model with a spatially structured random effect in R

There are n sampling units (with explicit spatial coordinates (pos_x[i], pos_y[i]), i = 1..n). Data is generated as: ...
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1answer
24 views

Spatial correlation and tolerance limits

I have previously studied the problem of defining tolerance limits for normal distributions for a given small sample of observations. Now I would like to take into consideration the fact that the ...
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12 views

Space-Time Scan Statistic

I need to perform an anomaly analysis in both space and time. I have 4 data parameters: latitude, longitude, time and temperature. What I’m trying to do is to find temperature anomalies that are ...
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17 views

Difference between exogenous and endogenous spatial autocorrelation

I was reading a paper recently and came across the following paragraph: Autocorrelated distribution patterns may arise in two non-mutually exclusive ways; endogenous autocorrelation is caused by ...
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10 views

spBayes for non fixed semivariogram parameters

I am considering a Bayesian Gaussian spatial regression model y(s) = x(s) b + w(s) + e where ...
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23 views

GMM post estimation tests

Within a 3 equation GMM model how do you judge the validity of your IVs? You really can't do what I have seen where people look at the first-stage of 2SLS models for each equation, because within GMM ...
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29 views

Hypothesis testing - significant differences in 2D spatial data

This question is derived from a previous post, but the problem has changed somewhat and more information is provided here. The challenge: In an actual experiment, 40 dice are dropped into a body of ...
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120 views

Interpretation of Mantel correlograms

i checked the presence of spatial autocorrelation in the abundance of species living in 10x10m plots, 60 samples per plot. I did vegan's correlog function with default bins (12 distance classes ~ each ...
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24 views

Critical scale of variation of tree biomass using variography

I have a combination of a philosophical and a technical question. I am interested in an application where I am trying to find a critical scale of autocorrelation of tree biomass on the landscape. ...
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22 views

Spatial sampling question

I have a research project where I need to sample census block groups. After I choose the sample, I have to survey each block group on foot and collect some physical attributes and analyze their ...
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18 views

Handling non-normality in the residuals of a spatial autoregressive model

I am performing a spatial autoregressive model (function errorsarlm in spdep R package). Although I tried a number of alternative variables transformations, the model' residuals are always non-normal. ...
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1answer
7 views

how to: realistic spatial matching

actually im trying to do some realistic spatial analysis with R. Therefore I create a random variable and I want to match them to a SpatialPolygonDataFrame. But I want it more realistic with the ...
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1answer
29 views

Spatial prediction on surface: very fine grid vs coarse grid + quick interpolation

Once I have fitted a spatial model (point-referenced data), I need to make a prediction map. A natural approach is to make prediction over a fine grid over the region. However, the required ...
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27 views

MCMC convergence with spBayes

I am running spBayes to fit a model like y ~ ID + 0 and I am using an exponential model for the spatial component. I am a bit confused on the outcome of the ...
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1answer
27 views

Spatstat package and Spatial point process: How to estimate the density when computing the inhomogeneous K-function?

http://www.inside-r.org/packages/cran/spatstat/docs/Kinhom Here we see that to get the inhomogeneous K-function, we can either use a kernel density approximation method with small bandwidth to ...
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24 views

Spatial point process: Homogeneous vs inhomogeneous K-function

I wonder when would you use a homogeneous K-function instead of a inhomogeneous one and what advantage it has over inhomogeneous K-function? In my opinion I think we should always use inhomogeneous ...
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25 views

Is there a recursive version of Kriging or Inverse Distance spatial interpolation?

Classic use-case of Kriging: you have a 2d space, you have $n$ observations, each of them representing an exploratory dig. It has a $x$ and $y$ coordinate, and a $V$ representing the value discovered ...
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1answer
45 views

Packages to fit and predict with time space dynamic models with custom spatial weights matrix

I am modeling the diffusion of a technology product across space and time. I am hoping to model the interdependence and influence between geographies directly, and use the model to forecast future ...
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26 views

How to fit 3D spatial model with categorical response in R?

At this stage, I am happy with either model-based or non/semi-parametric fit. It is a multinomial categorical response. Canfields do it? (either via ...
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11 views

Expectation maximization from distances

I want to infer location from noisy distance measurements from a sensor network. I've been doing initial simulations and trying to use EM to help. I have: A list of distance measurements to each ...
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13 views

Assessing variable importance in the presence of spatial correlation

I have a data set that consists of data from 300 plots. These plots are laid out in clusters so spatial correlation is an issue here. At each plot the presence or absence of a particular bird species ...
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1answer
66 views

What is the proper way of calculating the kernel density estimate from geographical coordinates?

I have to calculate the 2d kernel density estimate (kde) from a list of latitude and longitude coordinates. But one degree in latitude is not the same distance as one degree in longitude, this means ...
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22 views

Spatial correlated covariates with spatial correlated response

I like to estimate a linear regression model in a Panel data set using a fixed effects specification. From the data (and theory) I know that my response variable ($Y$) is spatial correlated. The same ...
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4answers
584 views

What does “irregularly spaced spatial data” mean?

When I read the paper “Multiscale methods for data on graphs and irregular multidimensional situations”, by Maarten Jansen, Guy P. Nason and B. W. Silverman, I find the term “irregularly spaced ...
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1answer
23 views

Extracting spatial covariance given only mean and variance

I have the results of an MCMC experiment in the form of a set of means $\mu(\phi,\theta)$ and standard deviations $\sigma(\phi,\theta)$ as a function of spatial coordinates $\phi$ and $\theta$ (in ...
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26 views

Using GAMs with limited spatial information to account for spatial autocorrelation

This question follows on from two previous questions; Why does including latitude and longitude in a GAM account for spatial autocorrelation? and Detecting spatial autocorrelation with limited spatial ...
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1answer
59 views

Regression-like models for spatial point processes restricted to a network or grid

I am working on a spatial analysis of traffic accidents, the goal of which is to estimate the effects of spatial covariates on the intensity function of crashes. The original analysis was an ...
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28 views

Spatial regression with misaligned predictor (point) and outcome (point)

My outcome (Y) is the type of traffic crash event measured at every intersection (on a street grid). Covariates are measured at the locations of the events. The predictor of main interest (X, a ...
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1answer
95 views

Detecting spatial autocorrelation with limited spatial information

I have some ecological data collected from n independent sites spanning a relatively large spatial scale (>10 degrees of latitude), and from each site, n replicate samples were collected but no ...
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3answers
163 views

Statistical model to predict the next move on network only using movement history

Is it possible to build a statistical model that predicts the next move in a graph solely based on past movements and the structure of the graph? I have made an example to illustrate the problem: ...
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1answer
21 views

Comparing X-Y Co-ordinates

I have 500 x-y co-ordinates with five different variables so around 100 for each variable. I would like to compare how packed the clusters are, also how far they are away from their desired points ...