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.

632 questions
12 views

Table generation from spatialreg models [on hold]

So, I estimated some spatial models using the spatialreg r package: A SLX, a SAR and a SEM model. Now I want to get coefficients and standard errors out; in the past I usually used either the ...
8 views

Spatial modelling: raster calculation from covariate estimates of GLMs produce some negative values in raster distribution data

I am constructing spatial distribution models/maps for soil carbon using coefficient estimates from a GLM. The GLM is made up of a mix of continuous and categorical variables and the response is a ...
16 views

Accounting for spatial autocorrelation in model - A simulation

My question, in short, is: I was trying to demonstrate that accounting for spatial autocorrelation reduces the overestimation of significance of a non-autocorrelated fixed effect. The result, ...
87 views

Spatial Point Process: Does an inhomogeneous first order intensity function affect the second order dependence?

As the title suggests, I am having a bit of confusion on the effect of first order intensity function. If I have a first order intensity function that says in a certain region the points are much more ...
9 views

compare a neighbourhood value with the city mean - test of significance in presence of spatial autocorrelation

I have a dataset with all neighbourhoods in a city and a value for each neighbourhood (a rate). I would like to be able to create a vizualization that enables the user to select individual ...
41 views

compare neighbourhood value with the mean value across all neighbourhoods in the city

I have a dataset with all neighbourhoods in a city and their poverty rates. I would like to be able to create a vizualization that enables the user to select individual neighbourhoods and find out ...
12 views

How to interpret lines crossing on Ripley's K plot

The image above (which I took from another post) illustrates one of the typical patterns in a K plot. It shows a Ripley's K plot showing the actual below the expected up until a radius of about .17, ...
22 views

Empirial Bayes for means

I have data for US ~3100 counties where the variable is a mean score based on a sample. However, for many small counties, the sample size is quite small (like 5), and so these mean values fluctuate a ...
47 views

How to test whether birds spend more time in specific areas along a time-segmented track?

I have geolocation data on birds with 1 position per day (latitude + longitude) plus I have for each day, a corresponding binary time series that takes values 0 or 1. There is periods of minimum 10 ...
8 views

why variogram models take only one independent variable

lznr.vgm = variogram(log(zinc)~sqrt(dist), meuse) i am using meuse data for practicing to create variogram models, but i am confused to know there are 14 ...
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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 '...
70 views

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 ...
16 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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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 ...
13 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 ...
8 views

Given data and covariance matrix in Euclidean space, how to compute covariance matrix in Polar forms without computing the sample covariances?

For 2D, given (x,y) data points, and the covariance matrix C, how to compute the covariance matrix in polar form efficiently without transforming all data to polar form first then compute the sample ...
32 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 ...
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 ...
135 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 ...
20 views

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 ...
26 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 ...
12 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 ...
43 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, ...
7 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 ...
25 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. ...
8 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 ...
23 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 ...
15 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 ...
38 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 ...
28 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, ...
65 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-...
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 ...
83 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 ...
79 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 ...
90 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 ...
17 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 ...
33 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 ...
61 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 ...
43 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 ...
30 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 ...
13 views

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 ...
29 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 ...
32 views

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 ...
19 views

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 ...
66 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 ...
123 views

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 ...
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 ...