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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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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
28 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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14 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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10 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 ...
3
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1answer
37 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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29 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
23 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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11 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 ...
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18 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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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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10 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 ...
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56 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 ...
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37 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 ...
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Spatial autocorrelation and predictive accuracy

Hi everyone! I have a training dataset of observations from nine river sites relating three predictors and one (known) response variable (K) and I am testing several algorithms (boosted regression, ...
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60 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
27 views

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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38 views

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
20 views

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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67 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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0answers
12 views

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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15 views

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 ...
1
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1answer
16 views

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 $s$ ...
3
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1answer
17 views

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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2answers
130 views

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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0answers
29 views

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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0answers
18 views

When to address spatial auto-correlation?

I am trying to understand when I should address spatial auto-correlation. Let's say that I have a number of weather stations in the mountains and an equal number of weather stations by the sea. I ...
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0answers
34 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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0answers
17 views

Calculate L-function envelopes from a fitted model: Lest or Linhom?

I have fitted a model to a point pattern using INLA, and generated 1000 simulated pp from the posterior of this model. I want to use these samples to generate the L-function envelope for my data, and ...
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1answer
56 views

Are kernel Density estimation and gaussian blur related?

I have a set of points in a 2d space representing location of animals. I am interested in a probability heatmap which give lower values for cells far from these locations. I have seen many ...
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0answers
28 views

Subsampling to account for spatial autocorrelation of observations

I'm wondering to what extent (if any) subsampling of observations can be used to account for spatial autocorrelation within data. Is taking a smaller sample (subsample) of observations (without ...
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1answer
52 views

How can I understand these variograms?

Using grf function from R package geoR, I simulated 6 replicates (each with 1000 samples) of a Gaussian random field on ...
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0answers
19 views

Is it common to decompose many time series in a business?

I am working in a industry. Most of the time I do statistical reports on sales. I'm new to time series analysis, so please be patient: the question might be obvious. I would like to monitor the sales ...
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0answers
53 views

Spatial Lag Model and Heteroscedasticity

I am using Spatial Lag Models with the form yi = ρWyi + βXi + εi, and am estimating these in R using spdep::lagsarlm. However, Breusch-Pagan-Tests using ...
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0answers
18 views

Dau Genton test - in grandmothers terms

tl;dr Can you explain the Dau Genton test in terms a median grandmother could understand? Background: So I am looking for an "in.chull" for multivariate, concave hull, and I was going through "...
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0answers
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Combining 2 different spatial datasets

I've tried to keep the formulation as general as possible. Problem: For a given location (e.g. a county, country), I have 2 different datasets (D1, D2) where the rows are of the form D1: ...
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67 views

Residuals' spatial autocorrelation in Boosted Regression Trees after correcting for it

I am running boosted regression trees (BRT) in R, with the package dismo and I have included a predictor (residual autocovariate) that, in theory, correct for spatial autocorrelation, following a ...
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1answer
30 views

How to measure the spatial dipresion of multiple clustered data

Context: My data are binary maps that represent the spatial distribution of events. Whenever an event occurs at a location, the pixel representing that location is assigned with the value 1. Below are ...
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40 views

Is it fair to use Evidence Likelihood-transformed variables in a Logistic Regression?

I am working on some logistic regressions in a land-use/cover change software called TerrSet. The dependent variable is deforestation (= 1) or no-deforestation (=0). In this case, input variables for ...
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How to define the minimum number of validations instances (points) in large imbalanced datasets

I have been reclassifying a polygon layer to transform Land Use data into Land cover data. Long story short: My final reclassification has about 100.000 polygons, and I need to manually validate them,...
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38 views

Find unbiased estimators for $\lambda$ and $\lambda^2$.

For the spatial homogeneous Poisson process, find unbiased estimators for $\lambda$ and $\lambda^2$. Attempt: Since the homogeneous Poisson process is over an area, how i would i go about ...
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0answers
18 views

Is this a legitimate correlation function?

Is the following a legitimate correlation function for a one-dimensional spatial process $S(x):x\in \mathbb{R}$? $$\rho(u)= \begin{cases} 1-u &: 0 \leq u \leq 1\\ 0 &: u>1 \end{cases}$$ ...
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30 views

Time series regression

I have a dataset of SO4 concentration (annually) from 1986-2016 across 35 water catchment stations. The dataset looks like this: I first plotted the data and found out that the trend pattern is ...
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41 views

Can you use spatial regression models to analyse survey data with a binary outcome?

I have a survey of about 2700 respondents distributed across 35 municipalities in the Netherlands, and I am modelling a binary outcome (voting for a political party) as a function of detailed ...
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33 views

Accounting for spatial dependence in conditional logistic or GLM paired regression

I am studying the factors that influenced the location of pre-Euro American settlement travel routes. To do this I am using a paired used/available approach. I have points where trails were observed ...
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13 views

Correlation of coordinates between unequal datasets

I was wondering, if it is possible to develop an automatic tagging system for football analysis. I have a N number of possessions of team A that include on the ball events occurred. Each event has an ...
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41 views

How to evaluate global and local effects in one model

I want to test the effect of elevation on the intensity of burrowing by gopher tortoises in flatwoods [a type of pine savanna characterized by both low (wet) and high (dry) areas]. However, in several ...
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1answer
82 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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0answers
21 views

Comparing measures of spatial autocorrelation in residuals

1) In different regressions Say first regression is: $y = \beta_1 x_1 + \beta_2 x_2 + u $ And the second is : $y = \beta_1 x_1 + \beta_2 x_2 + \beta_3 x_3 + v $ Are Moran's I values on residuals $...
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When compared to a multicollinearity regression, why does the P-value of a variable increase in significance when I run a spatially lagged model?

My hypothesis is: Self Reported Health is higher(positive) in neighborhoods with a higher density of Street Trees per mile of residential street in New York City. My dependent variable is Self ...
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How do I fit a Generalised Linear Mixed Model to 3D coordinate data, where the outcome is binary?

I'm trying to understand how I might fit a Generalised Linear Mixed Model (GLMM) to a data set comprising 3D coordinates, with a binary outcome. The basic set-up is as follows: Each subject has its ...