Questions tagged [spatio-temporal]
Describes data models with a time-series component and a spatial component.
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Neural network training with different data formats and predictors as inputs but both sharing same dimensions
I'm working with different types of environmental spatiotemporal data. They share a target variable and have the same dimensions (latitude, longitude and time) but they are expressed in different ...
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Contour plots of a patio-temporal covariance function
I would like to plot contour plots of covariance functions in R:
one for a fitted separable spatio-temporal covariance;
one for the empirical covariance function,
similarly to Figure 4.4 in Wikle et ...
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Analyzing geolocation and time of purchase data to determine the spatial provision strategy for a new product
I have a dataset containing geolocation and time of purchase information for buyers of a new product (Product X). I'd like to determine the unit of spatial provision when this product was offered to ...
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What are suitable statistical approaches to examine temporal variation of species abundance/ community composition across multiple sites?
I'm looking for appropriate types of analysis for a data set that contains counts of different crab species across 4 sites with 3 replicates per site (12 in total) over a time period of 1.5 years - 5 ...
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GAM setting k for spatial autocorrelation across scale
I am working with a bunch of different GAMs with predictor land cover and remote sensing variables derived at different scales and comparing models within scale. I am not interested in spatial and ...
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Simulating Space-Time Gaussian data in R with non-separable covariance function
When wanting to simulate Gaussian spatial data in R one can proceed as follows:
...
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How to reduce concurvity with space-time smooth in GAM?
In these notes, Simon Wood gives an example on how to tackle high concurvity when a spatial term is present in a GAM.
With spatial confounding it sometimes helps to increase the smoothing
parameter ...
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Basic Methods & Literature for spatio-temporal data
I'm new to the field of space-time related data.
The basic idea of the dataset is the following:
Say I have a map (e.g. USA) and data matrices that contain measurements at fixed positions (e.g. states)...
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Kernel Filter size and sampling frequency
I was wondering if I could understand the relationship between kernel size and sampling frequency. I was reading this paper and on Pg 6-7 ("In block-1" section), I read that kernel size of ...
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Geostatistics with different measurement errors
I'm having a hard time identifying the subject and possible resources of my problem.
I have spatio-temporal data (Z) coming from environmental sensors that travel around a city. We have the spatial ...
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How to compare the sensitivity of many countries?
My thesis question is asking whether biodiversity sensitivity differs geographically. I will assess all 5 pressures individually, but take 1 (pollution) as an example.
My data contains time series for ...
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Latent variables for spatio-temporal Extreme Value in R [closed]
Latent variables models are often used for spatial extremes modeling
see e.g., Davison, Padoan and
Ribatet. A typical application
use block maxima such as annual maxima of temperature, assumed to ...
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How to quantify temporal overlap of species abundance?
I want to compare the extent of overlap of species abundances in the following two secanrios. In the first scenario, species barely overlap so the index or overlap value should be zero. in the second ...
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How to deal with spatial autocorrelation AND temporal autocorrelation in a mixed model?
When creating a mixed model (or GLS) with spatiotemporal data, you can include correlation structure into your model to address autocorrelation. Spatial autocorrelation can be modelled for with ...
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ML Method for temporal object mapping
The scenario is like this:
I have 2 point clouds, representing the radar readings of a car at the moment t and t + 0.1 seconds. ...
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What is the best correlation test to use when you want to compare two variables in a spatiotemporal context?
I have 9 sampling sites. I did the sampling in May, July, and September in the sediments and the water. So, I have 27 samples. I want to know if there is a linear correlation between total nitrogen ...
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Spatial and time lag autocorrelation
I am designing an experiment to examine spatial autocorrelation within 50km of a point. The setting is the open ocean with sensors that take depth profiles of environmental data (Temperature, Salinity,...
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Modelling spatio-temporal data with repeated measurements
I would like to perform regression on an environmental dataset. The covariates are in the following form
I realize that the 4 repeated measures for each region are dependent because they come from ...
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How to perform PCA analysis on space-time data for few species in R? [closed]
The data-set I'm looking to analyze has 6 sites. Each site was sampled at five unique locations each month for a year. We could identify abundance of 4 species across the data set. Together, I have ...
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Clustering data with temporal effect
As an example of a dataframe, we could think a problem such as:
(my real table is much bigger and with a lot of ID_PRODUCTs and a lot of ID_CLASS_PRODUCTs)
ID_CLIENT
DATE
ID_PRODUCT
ID_CLASS_PRODUCT
...
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How to best impute missing values of county-level time series data using R?
I have a dataset consisting of mobility data at the county-level for the US for about one year. So the number of observations is >1m. Apart from the county code, the date, and the mobility index, ...
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Classification Accuracy with Temporal Component
Problem
I have a 3D matrix of time-series, it's a spatial dataset with the 1st and 2nd dimension being x and y and the 3rd dimension being time. Some of the time-series have a structual break in them ...
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Comparison between two times series
I am looking at time series data, comparing the velocity with which different groups of animals move in a new environment. In its raw form, the data consists of trajectories from individual fish that ...
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Interpreting a Distance & Time 3D Variogram for Variogram modeling
I am trying to understand some concepts of variograms. I have made several variogram models in R and am trying to understand exactly what they mean. My data is ...
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What is the best technique to determine Spatio temporal correlations?
I have Carbon emissions data for 20 years for different regions in a country. I want to test the hypothesis that the emissions are statistically different for the regions over the 20 year period. What ...
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Best Statistical Techniques for Order Sensitive Data
Problem
I am writing a Genetic Algorithm (GA) that aims to find the best order of performing a given set of tasks to fulfill an objective.
Imagine there are a set of tasks ...
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Why do we need to model max, min, and average temperature for infection disease [closed]
For COVID-19, I read many papers who try to find the relationship between COVID-19 and temperature. In these papers, the authors found the relationship between daily confirmed cases of COVID-19 and ...
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Spatio-temporal autocorrelation
I have a huge data frame (300k + rows) on GPS animal positions.
I want to model the probability of the presence of chamois taking into consideration as variables: distance (from a disturbance), ...
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Is the COVID-19 pandemic curve a Gaussian curve?
We've all heard a lot about "flattening the curve". I was wondering if these curve – that look like bells – can be qualified as Gaussian despite the fact that there is a temporal dimension.
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Modelling count differences on irregular lattice
I have the following dataset. I have a time series over an irregular grid where for each position in the grid, there is a variable that for each point in time counts the cumulative difference between ...
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What relationships do spatial statistics share with time series analysis?
Spatial statistics is often discussed in tandem with time series. How are the two related? Do they share methodologies? Do overlap in assumptions or conditions of data?
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Panel data regression (R)- temperatures at weather stations correlated across time and across stations
I have a balanced panel dataset with a few dozen weather stations' hourly temperature readings across several decades. I have a measure of population density around the weather station over time as ...
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Posterior Predictive CARBayesST
I'm trying to use the CARBayesST package and I need to do Spatio-temporal predictions. In the vignette of the package on page 27 says " If there had been saying m missing values, then the Y component ...
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SpatioTemporal regression
I have a data-set containing rain value for 6 stations and station coordinates (lat,lon). I used lm function taking lat,lon,day, their interaction and rain as below:
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What is the best way to model a spatialtemporal (3d) problem?
A very common problem in machine learning is that we have time variables. For this we use more statistical approaches like ARIMA or more ML approaches like LSTM.
A sophistication of a time series is ...
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Inference from small sample size with aggregated country data
I have a data set with country aggregate patient data for yearly total number of diseases, treatments provided by health services, and some other covariates for two countries over 10 years. The ...
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Is there something wrong with my Bayesian hierarchical spatio-temporal model?
I built a Bayesian spatio-temporal model and one of the parameters to be estimated is the random spatial effects s. The random spatial effect is assigned an intrinsic conditional autoregressive prior (...
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multivariate time series analysis with interactions among multiple dependent variables
I have been playing with time series data and using models like facebook prophet which uses time series decomposition and models the signal using trend, seasonalities and holidays.
The stuff I found ...
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Can I use a bayesian spatio-temporal model in cluster areas I chose from local Moran's I?
I have crime rates for municipalities in a state with hourly frequency. I want to make predictions about the spatio-temporal behavior of that variable. Is it possible to run a local Moran's I to ...
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Dimension reduction for multivariate spatio-temporal data for hurricanes forecast
I have weather data for the 40 previous years and for each year I have information about the hurricane season (intensity, number of active days, casualties,...). My ultimate goal would be to forecast ...
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Model for spatiotemporal and discrete variables
I have a situation where I am monitoring events at 50 or so geographical sites in a town and at each of these sites, I am making measurements regarding the count of certain particles (so the ...
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Is Hellinger transformation suitable for repeated (in time) site-species abundance data?
I have fish survey data from four different years and several locations, where I would like to study the difference in abundance and biomass between sites and check whether time dependence influences ...
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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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Covariance structures in glmmTMB for temporal autocorrelation
I'm running a zero-inflated, mixed-effects negative binomial model with the glmmTMB package in R.
My current format:
...
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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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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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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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How to calculate temporal change over time when response is 0 or 1 in r
What would be the best approach to calculate the temporal change in response that has values 0 or 1 over time? For example, I have data df with years ...
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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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How does Markov random field (bs=mrf) in mgvc gam handle repeated measures on the spatial units?
I am attempting a spatio-temporal model in mgcv gam.
I am using a factor smooth to define each of 27 areal units in a shapefile ("id") as subjects (essentially) which have undergone 23 repeated ...
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