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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45 views
Territories from observations
I have a number of animal observations, and want to deduce the number of territories (i.e. the number of individual animals) from this.
More formally, the problem can be stated as follows: Each ...
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0answers
35 views
How to test the effect of variable on spatial distribution of points in R
I'm trying to find statistical test (or procedure) which is able to discover patterns in spatial distribution of points. I sketch the problem by giving the example about position of bird territories ...
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0answers
77 views
Fit Gaussian random field for spatial data
I'm dealing with spatial data where the response variable is the gas concentration. In addition, I've the x,y-coordinate values, and another covariates. I'm thinking to fit a Gaussian random field ...
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0answers
14 views
Spatial interaction model calibration question
I am attempting to calibrate (i.e., estimate the parameters of) a spatial interaction model where one of my interaction terms is a composite of other terms. An example might be $I_{ij}$ = ...
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0answers
30 views
Modelling data of the form streets,timeofday,distance,duration?
I have data in the form of street name, time of the day, weekday/weekend, distance, duration for a lot of streets. I also have association of I went from street 1 to street 2 in a trip . For example:
...
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1answer
105 views
Stationarity - assumptions and examination
I am examining rodent captures on six permanent rodent trapping grids measuring 150 x 150 meters and consisting of 121 trap stations evenly spaced 15 meters apart. There are six such trapping grids ...
4
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1answer
58 views
Testing for non-random overlap of polygons
I have two polygon shapefiles and I want to see to what extent the observed amount of overlap is due to chance.
I'm thinking of some kind of permutation test, but not sure of the best way to ...
5
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1answer
87 views
Pattern recognition techniques in spatial or spatio-temporal data?
I am working with weather forecasters and have access to historical climatology data. Given current weather conditions in an area of interest (i.e. the current "map"), we want to try to find the most ...
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36 views
Fast/parallel alternative to GLS with nlme?
I am using the gls function from nlme to fit a fixed-effects model yet correct for spatial autocorrelation. My dataset has about 100,000 unique geographic observations, and running the following ...
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15 views
Number of areas in conditional autoregressive models
This is a simple question on Bayesian spatial modelling via conditional autoregressive modelling.
What is, according to your judgement (and possibly some methodological source), the minimum number ...
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0answers
23 views
Correlation in space (influence of building function on number of people passing through some point)
I am in a need of solving such problem: I have two data sets: number of people passing nearby some point in space (two points were analysed) and the function of buildings around those points. How do I ...
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1answer
47 views
need derivation of join-count variance (spatial autocorrelation stat), know where it is?
I am using interlibrary loan to get Cliff and Ord's book Spatial Processes, but the semester just ended and it is slow now. On page 18ish of this book, Cliff and Ord show how the variance for the ...
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0answers
53 views
Is there an R package for nonlinear mixed effects model with spatial autocorrelation?
I want to fit a nonlinear mixed effects model for repeated measures data. The subjects on which the measures were repeated are spatially structured. Is there a package in R for this? I also have ...
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2answers
105 views
What does the Semivariance tell me?
I am looking at a Semivariogram. I know it shows me the relationship between distance and semi-variance. I also know that at the end of the range the distance no longer auto correlates. What I am ...
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0answers
33 views
Hilbert curves: bounds / probabilities of preserving neighbors
Hilbert Curves (Wikipedia) are space-filling curves said to "fairly well preserve locality".
Do you know any theoretical results here, such as bounds that neighbors within a radius of $\varepsilon$ ...
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0answers
45 views
regression: handling negative autocorrelation in R?
I am running a regression in the R package nlme (but am not constrained to only that package). I am changing the spatial scale of the analysis over a few regression runs as a form of sensitivity ...
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1answer
80 views
Ripley's K Function and L Function for Point Patterns
The following is a spatial point pattern:
and these are the corresponding Ripley's K function and L function for this data:
How are these functions interpreted?
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1answer
68 views
Tests for spatial stationarity (homogeneity)
There are many models for spatial point patterns and spatial marked point patterns that assume spatial homogeneity or stationarity.
i) Is there a statistical test for determining this, where the ...
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2answers
134 views
Account for spatial autocorrelation with a binomial regression model
I am using a binomial regression model for presence/absence, with 20 independent variables to test. The data has x and y coordinates and I would like to understand how can I take into account the ...
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0answers
138 views
Pros and Cons of Fitting a Spatial Regression to Cumulative Data
When using regression to estimate a relation between a variable of interest and distance from a certain point (eg a distance-decay curve), what are the advantages and disadvantages of fitting the ...
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2answers
171 views
spatial autocorrelation for time series data
I have a 20-yr dataset of an annual count of species abundance for a set of polygons (~200 irregularly shaped, continuous polygons). I have been using regression analysis to infer trends (change in ...
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1answer
150 views
Hypothesis test on data with confounding spatial clustering
This is a bit of an elaboration on a question I posted earlier, since I feel like my approach to the problem as a whole is probably quite flawed.
Suppose I have a set of treatment and control cells, ...
2
votes
1answer
48 views
Filtering outliers from geo-spatial-temporal log
I have downloaded my Latitude location history from Google for the time of about three years and now I'd like to, for starters, visualize where I've been.
It turns out that the history contains some ...
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39 views
Measuring distance between geographic coordinates among other variables
I am setting up a quasi-experimental design and I need to compare each treatment account to all potential control accounts within a certain geographic region. I would like measure the distance ...
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0answers
51 views
Modeling spatial correlations with multilevel data
I have ~5M records of spatial polar coordinates (r and theta). These 5M records are from 400 different 'locations' that I have ~150 variables for (no NAs). I also have 1 binary variable used to flag ...
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0answers
46 views
Dealing with bias when aggregating spatial data
I've got a situation where I'm interested in $\Delta Y_{xy}$. This is calculated as $\Delta Y_{xy} = Y_{xy} \times change_{xy}$. Everything is vector-valued. I've got vector data on $change_{xy}$. ...
4
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1answer
101 views
Are there models for “censored” spatial point processes?
This is a problem I'm encountering in the context of analyzing a data set comprised of all crime locations in a city over a fixed time interval, although it could potentially arise in other types of ...
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2answers
71 views
How to analyse several types of geo data together?
I have some data gathered from a survey conducted within my city. All responses include an approximate geo location of where they were gathered (accurate to probably a couple of hundred yards which is ...
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1answer
35 views
Help me figure out the profile likehihood given this covariance function
I'm taking a spatial stats class, and I'm on the road so I can't ask the prof for help. Would appreciate help understanding what is going on here.
The problem is set up with $Y = X_s'\beta + e$ ...
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0answers
127 views
Spatial autocorrelation of non-homogeneous point data in irregularly shaped sample plots
Let's assume we registered the position of all individuals of different plant species within 3 irregularly shaped sample plots that are very close the each other. As an example, I put 2 pictures with ...
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0answers
64 views
Generating data using grf and plotting its variogram- Result intrepretation
I have a question about the semivariogram plot:
Suppose I generated 50 data points from Gaussian random field (using grf function in R), and assumed that we have exponential covariance model with ...
3
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2answers
212 views
Using Anselin Local Moran's I Values in Regression
I am doing a multiple linear regression of factors related to poverty and would like to include some spatial-statistical data. I have come up with Anselin Local Moran's I values (cluster/outlier) data ...
6
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1answer
139 views
Suggested books on spatial statistics
What are some of the best books for studying
i) variability of univariate and multivariate variables (real, count data) across a spatial domain.
ii) sampling a univariate or multivariate variable ...
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0answers
31 views
Possible outcomes of approximate profile-likelihood estimator (APLE) for spatial autocorrelation
I've been working with spatial autocorrelation for a while and now I'm trying to move from more traditional estimators such as Moran's I or Geary's C to the new APLE estimator. I read Li's papers on ...
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0answers
178 views
Spatial autocorrelation versus spatial stationarity
Let's assume we have points in two-dimensional space, and we wish to measure the effects of attributes $X$ on attribute $y$. The typical linear regression model is of course
$$y= X\beta + \epsilon$$
...
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46 views
How do I extend Inverse distance weighting to take into account uncertanities?
From a Multibeam echosounder (MBES) I have n x m measurements:
{(xi,yi,zi,di)}_i where (xi,yi,zi) is the location of the i'th reflection from the seafloor and di is the distance of the i'th reflection ...
3
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2answers
157 views
Auto crop black borders from a scanned image by making stats about gray values
I'm writing a computer program to automatically detect black noisy borders on scanned images and crop them off.
My algorithm is based on 2 variables: gray mean value (of the pixels in a rows/columns) ...
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0answers
77 views
Confusion related to bayesian spatial scan statistics
I was reading this paper related to bayesian spatial scan statistics. http://books.nips.cc/papers/files/nips18/NIPS2005_0513.pdf. It's said that when we use bayesian spatial scan statistics, we don't ...
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0answers
241 views
How to specify in r spatial covariance structure similar to SAS sp(pow) in a marginal model?
I'm currently translating existing code from SAS to R. I'm working on longitudinal data (CD4 count over time). I have the following SAS code :
...
2
votes
1answer
55 views
MLE estimation of spatial effects radius
I am trying to identify the maximum likelihood estimates in an SDM model (a hedonic home price model, with observations being 5,000 individual homes),
$$y=\rho W y + X\beta + WX\lambda + \epsilon$$
...
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38 views
Problems with spBayes package and prediction
I have successfully fit a number of spatial models with spBayes and am now trying to test their out of sample predictions. However spPredict always seems to fail with Cholesky decomposition errors. ...
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1answer
136 views
GLM and GAM package alternative to GRASP in R?
I am looking for the best package providing Generalized Linear Models (GLM) and General Additive Models (GAM) for spatial data. The most widely recommended (GRASP) is no longer current in the ...
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0answers
182 views
Compute Moran's I or some other estimate of spatial correlation in R
I'm trying to do a little spatial analysis--just some simple spatial correlations. I have a data frame consisting of latitude and longitudinal points, a value to model, and a neighborhood indicator. ...
5
votes
1answer
145 views
Computing confidence region for Gaussian mixture model
I have a 2-d Gaussian mixture model and would like to compute a confidence region for it. Our application is that the two dimensions are latitude and longitude; that is, we want to say something like ...
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0answers
12 views
Test for two - dimensional uniform distribution? [duplicate]
Possible Duplicate:
Measure the uniformity of distribution of points in a 2D square
I have spatial data -coordinates on rectangle, how to test if they come from two dimensional random ...
2
votes
1answer
54 views
Which metric use for problem of clustering spatial data of wind direction and speed?
I have two dimensional spatial (x,y - coordinates of meteo stations) data for small region (so I could neglect the shape of earth globe), for each (x,y) I have one observation of wind direction and ...
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3answers
599 views
Measure the uniformity of distribution of points in a 2D square
I have a 2D square, and I have a set of points inside it, say, 1000 points. I need a way to see if the distribution of points inside the square are spread out (or more or less uniformly distributed) ...
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3answers
224 views
Clustering with 3 attributes
Please bear with me because I am very new to data mining.
I have a database of 3 attributes: latitude, longitude and temperature. I want to find clusters for the temperature data and I also want to ...
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1answer
109 views
Generating spatially uncorrelated random fields in R
I have a DEM (cellsize 10x10 and cells.dim 450x300)
and I need to create 100 random error grids
that have the same dimensions as the DEM.
The values in the error grids are generated from a
normal ...
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0answers
71 views
Calculating R-squared values from a semivariogram
I have some spatially autocorrelated vegetation data, and would like to know the how well tree size measured at one location can predict tree size in plots 100m away.
I've made a semivariogram of ...
