Questions tagged [spatio-temporal]
Describes data models with a time-series component and a spatial component.
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What is the terminology for data aggregated via summed totals versus data aggregated via means?
The two types of data differ in that if you decide to decrease the temporal (time) resolution of the first type of data you take the mean of lower the resolutions. With the second you take the sum ...
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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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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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Do autocorrelated residual patterns remain even in models with appropriate correlation structures, & how to select the best models?
Context
This question uses R, but is about general statistical issues.
I'm analysing the effects of mortality factors (% mortality due to disease and parasitism) on moth population growth rate over ...
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Ways to reduce high dimensional data for visualization
I'm working on a 2D physical simulation and I am collecting data in time at several points. These discrete points are along vertical lines, with multiple lines in the axial direction. This makes the ...
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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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How to predict using Spatial temporal hierarchical bayesian models
I am using the R package CARBayesST to fit a Spatial-temporal Bayesian models. I want to use piece-wise ST model proposed by Lee and Lawson, 2017.
The package does not have a built-in predict ...
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Some help to get started with Spatio-temporal data analysis on different engines
I will soon receive experimental data from $n$ engines ($n$ is small, say, 10) for sensor data at the locations in figure:
As you can see, each engine is equipped with $5\times8=40$ sensors, ...
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Spatial autocorrelation (SAC) while analysing survey data
I am confused about some aspects of spatial autocorrelation usind survey data (survey which is repeated every year). I have data from 1991 to 2012 with sampling region pretty consistent every year. I ...
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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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