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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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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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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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Bayesian Prior in r glmmfields [closed]

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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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
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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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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
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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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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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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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1answer
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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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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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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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1answer
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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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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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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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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
34 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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51 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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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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1answer
56 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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2answers
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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
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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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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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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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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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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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Spatial Poisson model correlation structure

I'll preface this by saying I'm VERY new to this spatial epidemiology world. I'm running a spatial poisson model and have set its correlation structure as exponential. However once I arrived at my ...
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Spatial-grid data over time: check whether time series grids are temporally stationary

I have time-series spatial grid data, represented either as matrix or rasters. And I would like to assess whether they are temporally stationary or not. Do you know any test or R package that could ...
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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 ...
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What is the posterior kernel lengthscale of a Gaussian process?

If I have access to multiple samples from a Gaussian process with known covariance kernel but unknown parameters (i.e. unknown lengthscale), it is straightforward to estimate the lengthscale using ...
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242 views

Point process - intensity function vs probability density function

Suppose we have a point process in $\mathbb{R}$ with intensity $\lambda(x)$. Then, for a given compact set ${ S}$ we have $$\Lambda({ S})=\int_{\rm S} \lambda(x) \, dx,$$ where $\Lambda({ S})$ is ...
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1answer
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How to get the density estimate for the whole region based on data from several locations?

I am collecting air pollutant data for every area in a region. The available data I can find only has the data from stations in a few areas. Is it possible to estimate the air pollutant density for ...
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How to compare mean and standard deviation of two different spatial distance calculations?

I am calculating spatial distances between two 3D datasets formed by xyz points in two different ways: In the one way I am calculating the shortest distances between each point in dataset A (red ...
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1answer
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Is the assumption of indepence only for the sampled values informing the regression, or should it also apply to the cells of a prediction grid?

I have 200 discrete, well-spaced plots with reasonably independent sampled values from which I've derived a regression equation. If I use it to predict values on a similarly sized fishnet grid, how ...
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136 views

Problems fitting a model to a variogram

I am having problems fitting a variogram model. I tried to change some parameters to estimate or fix them but I am still not achieving any improvement. I remove trend of the data and use logarithms ...
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Geometric Mean Bias result for air quality models

i'm calculating the Geometric Mean Bias (MG) for the results of an air quality dispersion model against observations with the following equation from Chang and Hanna (2004); $MG = exp(\overline{LnC_o}...
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Plant density and spatial relationships

I have an experiment that investigates the affects of small mammal presence (present or absent) and fire (burned or unburned) in a replicated full factorial block design (4 plots--each treatment combo ...
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1answer
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Display uncertainty on spatialy distributed proportions (visualisation)

This question is related to Distribution of estimator of multiple (spatially related) proportions. We consider here the /visualisation/ issue. Consider a spatial random process $Z(s)$, where $s$ ...
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1answer
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Distribution of estimator of multiple (spatially related) proportions

Consider a spatial random process $Z(s)$, where $s$ denotes the spatial location. Our objective is to delineate the zone $\mathcal{Z}$ where the probability that $Z$ exceed a given threshold $\zeta$ ...
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Trajectory clustering - preprocessing and algorithms

Context Consider the following problem where we have two time dependent (yearly) measures: Fertility rate Life expectancy And a dimension: country. In other words we have over two hundred "...
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Spatial regression with overlapping areas

Is it statistically correct to calculate a regression with overlapping areas? I have market areas as the spatial unit with different sociodemographic and (macro)economic variables and I´m examining ...
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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 ...