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Questions tagged [spatial]

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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How to compute measures of dispersion and statistical significance of the impacts of a panel Spatial Durbin model (SDM)?

I ran a panel Spatial Durbin model (SDM) and computed the summary measures of impacts (direct, indirect and total). Now, I would like to get measures of dispersion for the impacts estimates as well as ...
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Neighborless regions in hot-spot analysis -GeoDA

I am performing hot-spot analysis on aggregate data in the 632 districts of India. The hot-spot map produced by GeoDA software, using Queen's contiguity weight matrix identifies 5 districts as '...
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Bayesian spatial autoregressive (SAR) model with heteroskedasticity in R

In socio-economic data, I always found heteroskedasticity that can't be solved using transformation.I had read a paper "Spatial autoregressive models with unknown heteroskedasticity:A comparison of ...
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36 views

Can a filtration be not monotone increasing?

A stochastic process $X_t$ is defined on a filtration $\mathcal{F}_t$, which is an increasing sequence of sigma fields. As I understand, this guarantees that any $X_s$ will be measurable w.r.t. $\...
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1answer
2k 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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12 views

How to adjust for spatial autocorrelation in panel regression in R

I am running a panel regression with two-way fixed effects, the outcome variable being the number of conflicts in each district each month. My calculation of Moran's I seems to indicate that the ...
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3 views

Distance based Spatial sampling

I am struggling with spatial sampling of data which has Latitude & Longitude for data points. I need to do sampling such that no adjacent or nearby point should get selected ( Need to give some ...
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13 views

Bayesian Prior in r glmmfields [on hold]

I am making a foray into looking at Bayesian approaches to spatial modeling for the first time on some wildlife presence/absence binomial data with a glm. I am trying to work with the glmmfields ...
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485 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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12 views

How to best evaluate the quality / precision of geo-spatial prediction?

I have developed an algorithm to predict locations of certain items in 2D-space. The input data consists of various fuzzy / blurred observations of those items. Therefore, I am not performing a binary ...
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12 views

How to deal with non-stationary spatial autoregressive model

I wonder what to do in case a spatial autoregressive parameter is found to be unity. If in time series econometrics a unit root is detected, differencing the process helps. Is there something similar ...
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1answer
31 views

Identifying good areas in a two dimensional graph

I have a an outcome variable with three states: win(green), lose(red) and draw(gray) and a sample of data points, each with a value on two independent variables x and y. I can plot the outcomes using ...
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1answer
105 views

Ripley K function value in a specific radius and dataset using R's Kest function

I'm having general trouble with calculating Ripley's K function values. The following is a simple spatial point pattern, where both X and Y range from 0 to 200: Here's its corresponding Ripley K ...
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37 views

probability involves bivariate gaussian

I'm working on a spatial project. I need to calculate the probability of a point being the closest to another. Say I'm given four points $y$, $x_1$,$x_2$ and $x_3$ in 2D plane, and let $Y'=y+Z$, where ...
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1answer
208 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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1answer
201 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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1answer
7k views

40,000 neuroscience papers might be wrong

I saw this article in the Economist about a seemingly devastating paper [1] casting doubt on "something like 40,000 published [fMRI] studies." The error, they say, is because of "erroneous statistical ...
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Comparing 3 raster maps of continuous surface data in R

I have 3 maps representing spatial distribution in hunting pressure. These maps were derived using different methods and I am now interested in comparing them to assess how they might differ/agree ...
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1answer
119 views

Clustering spatial data based on location and values

I'm looking for a way, preferably in R, to create a cluster of point data (specifically, the centroids of UK postcodes), where each cluster comes as close as possible to containing a certain number of ...
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1answer
227 views

Assessing spatial autocorrelation in structural equation models

I have a SEM built with lavaan and I would like to assess spatial autocorrelation. I found this code written by Jarrett Byrnes that does exactly that: http://www.imachordata.com/space-and-sems-2/ ...
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1answer
9 views

Estimating population concentrations in spatially autocorrelated data

I'm stuck on which statistic to use with a spatial data set to resolve population concentrations in a large area, when I have only sampled a small area relative to that large area. Here's an example ...
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24 views

Inhomogeneous K-function to indicate need for spatial dependence/interaction term in Poisson point process model

I am mapping and modelling a disease of sheep. I have approx 4200 point locations in my dataset, each of which represents the centroid of a given sheep farm. I have created a K-function difference ...
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2answers
415 views

How to compare GLS models?

I have spatial data set for 35 studies. In each study, there are variables y, x1, x2, latitude, and longitude. I want to know whether adding x2 to model y~x1 will improve the simple regression model y~...
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1answer
41 views

Does standard distance follow the 68-95-99.7 rule?

I'm wanting to do a simple standard distance demonstration for my students in R, but I've come across a conundrum. When I simulate the creation of 10,000 points in a spatial normal distribution, ...
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6 views

Spatial clustering of ordinal attribute

I have a set of polygons (ESRI shapefile), each with one ordinal value. The values are in the range of 1 to 100. Not all values within this range are used and there can be repetition of values across ...
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37 views

Linear model from iterative process in R

I would like to test a relationship between to factors such as birds occurrence and temperature for instance, to test if temperature affects birds occurrence from a country (e.g. Germany). I have a ...
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1answer
391 views

How to interpret LISA clustering maps?

I have produced a LISA clustering map showing the types of significant clustering of the proportion of part-time workers in London: However, as I understand it, 'low-high' describes an area of low ...
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1answer
20 views

How to estimate the leafsize of the kd-tree?

The kd-tree implementation proposed by the scipy python libray asks for the value of the leafsize parameter that is to say the maximum number of points a node can hold. It is by default set to 10. ...
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7 views

Comparison of multiple spatial model predicted outputs

I am performing some species distribution model comparisons under different sampling strategies. I have two sampling constraints with five levels (e.g. presence sample sizes), for a total of 25 ...
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21 views

Using Markov random field spatial weights to account for spatial autocorrelation

I am looking at the relationship between life expectancy and smoking rate within the London boroughs. I thus created a bayesx spatial regression model including a term which assigns spatial ...
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1answer
94 views

Disaggregation of spatial autocorrelation parameter

I have data aggregated at state level. When I estimate a spatial autoregressive model such as $$y = \rho W y + X\beta + \epsilon$$ on this data, I see that the autoregressive parameter $\rho$ is ...
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13 views

How to ensure independence of calibration and validation data a spatial model considering spatial autocorrelation?

I determined the vegetation type (4 types all in all) at 120 points (stratified random sampling) in my study area (650ha). I want to use the points to train a statistic model (eg. random forest) based ...
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1answer
33 views

Spatio-temporal convolutional networks on irregular grids

I'm contemplating a project where I try to take a time series of maps of polygons (which have values) and predict the next map of polygon values. If it were a regular grid, it'd be a ...
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27 views

How can I find a representative point in 3D matrix (time,lon,lat)

I have temperature in a matrix of time, longitude and latitude. I need to find a way or criterion to find a point or location (lon *, lat *) that is representative of my entire area of interest (time, ...
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50 views

Unexpected behavior in inhomogeneous Cross K Function (Kcross.inhom) [closed]

I am currently analyzing a point pattern in R using the "spatstat" package. I am comparing two different areas, therefore I made two plots for each area (first two plot-left-area1; second two plots-...
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1answer
51 views

Performing random forest on spatio-temporal rasters

We are trying to train a random forest model on land-use and meteorological variables to predict daily concentrations of air pollution at a 1km resolution. Our input data consists of 1km raster stacks ...
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15 views

Help with fitting a panel regression model

How can I fit a panel model in which the outcome of interest, i.e., the dependent variable is at the county level and one of the explanatory variables is at national level? (e.g. The effect of a ...
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2answers
68 views

Testing for randomness against Poisson distribution - what is the null hypothesis?

"This week, we examined the simplest theory of spatial criminology – that crimes are distributed at random. When spatial criminologists want to test observed data for randomness, they test that data’s ...
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1answer
80 views

Implementing a regression tree based on differences between estimates

I am currently working on a class project, in which I need to identify groups of regions in my sample base on a regression tree. However, I am unfortunately not very familiar with regression trees in ...
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1answer
85 views

Point Pattern Analysis: Assumptions for Hopkins-Skellam Index

I am currently analyzing a point pattern in R using the "spatstat" package. My analyses are primarily exploratory, as I do not have any strong reason to suspect either clustering or regularity, though ...
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1answer
113 views

Quantifying how uniformly spread out points are?

I'm looking for a way to quantify how "clumped" vs homogeneously/uniformly distributed points are in a graph. Each collection has 100 points as (x,y) pairs. I've attached two graphs as an example. ...
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5answers
12k views

2D analog of standard deviation?

Consider the following experiment: a group of people is given a list of cities, and asked to mark the corresponding locations on an (otherwise unlabeled) map of the world. For each city, you will get ...
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16 views

Considerations When Using Lat/Long Cords on Classifier

I'm interested in using Latitude and Longitude points as features to build a classifier model, but would like to better understand if I need to be taking any precautions when using Lat/Long cords in ...
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25 views

Spatial Analysis with Repeated Measures

I am doing an agricultural study in which I analyzed parameters of fruit and treated them with different conditions. The fruits were measured once a week for four weeks. Now, I would like to know if ...
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1answer
44 views

why does ignoring spatial autocorrelation lead to spurious significance

In spatial statistics one often hears the statements like the following: unaccounted for spatial autocorrelation may lead to spurious significance / understimated uncertainty / too narrow ...
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0answers
40 views

Gaussian random fields: matrix and convolution sampling

I should be able to generate a stationary GRF from white noise in two different ways: multiplying the white noise vector by the square root of a covariance matrix with appropriate kernel; taking the ...
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1answer
28 views

Standard population for SMR estimation

I have deaths by counties from 1980-2010 by age and sex. I want to calculate the SMR and then map the rates. My question is what standard population should I consider. If the SMR is Yi (# deaths ...
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Should a nugget ever shift the variogram away from zero at distance zero?

I had frequently seen the definition for a "rigorous" spatial isotropic semivariogram being defined as: $$ \gamma(h) = K(0) - K(h) $$ Where $K$ is a positive definite covariance matrix. If the ...
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24 views

How do nugget interactions work in Gaussian Processes/Kriging?

How do nuggets and nugget interactions fit into the variogram framework? I am especially interested in the case where there is more than one distance term being used (e.g. space and time): where you ...
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63 views

Spatial regression: random and fixed effects [closed]

I'm working with spatial data (two rasters or matrix in the attached Figure), that is distributed in a 2D-space and each grid has a value. The two grids have the same number of cells. Variable "Y" is ...