# Questions tagged [point-process]

A point process is a stochastic process in which the data are sets of points ordered in a mathematical space. A common example is the Poisson process, in which points are ordered in time with the interarrival times exponentially distributed.

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### Maximum Absolute Deviation Test - Change of rank?

For the point process finpines (standard data set of the spatstat library), I would like to verify whether it satisfies the ...
0answers
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### Spatial point pattern modelling where the observation of points are uncertain?

I am wondering if there is any literature on this issue. My problem here is not regarding the location uncertainty of the points, it is rather that I am not sure if a point is indeed an event ...
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### Knowing when to stop with spatial point thinning — is an approach with Clark-Evans test valid?

I need a random sample of presence points from the species' area to use in distribution modeling. I have an excessive amount of spatially clustered presence records, so I use minimum nearest neighbor ...
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### Is Nearest Neighbor Distance Ratio (NNDR) test good for assessing point pattern?

Regularity of point pattern is routinely checked in ArcGIS with the Nearest Neighbor Distance Ratio test providing significance estimations: https://pro.arcgis.com/en/pro-app/latest/tool-reference/...
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### Best models to relate a frequent point process and a rare point process

I want to relate two processes and understand their cause-and-effect relationship. The first process is a point process with frequent occurrences (more than 90%) and has support [0,1] and truncated ...
1answer
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### Predict background counts given past observations and assumption of linear variation of the rate parameter in time

Consider the following problem. We have a time series of counts (poisson-distributed) data. In this time series we can select an off-pulse window in which only background is present and a subsequent ...
1answer
34 views

### Simple point processes and the expected value

When considering simple point processes, how is $$P(t_{n+1} \in [t;t+dt]) = E[N([t;t+dt])]$$, where $N(A)$ is the number of points in interval $A$ and $dt$ is the length of an infinitesimal interval. ...
0answers
19 views

### Log Gaussian Cox Process with multi-scale cluster (non-stationary covaraince structure)

As the title suggests, I am working on point patterns that exhibit highly varying sizes of clusters. This kind of data arises mostly in astronomy where 3d point patterns are projected onto 2d space, ...
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### Can random effects be used in the spatial LGCP package (from JSS paper by Taylor et al. 2015)?

I am reading the excellent statistical software paper found here in this link. The paper is an R implementation of Log-Gaussian Cox processes for spatial point process applications. Whilst the ...
1answer
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### KS Test for Hawkes Process

I am analyzing some data by applying 1d-Hawkes processes. To evaluate the fit of the model itself (and particularly the chosen kernel, i.e. exponential), I am performing a KS test. However, it is not ...
0answers
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### spatstat::plot.envelope observed line longer than significance band [duplicate]

Using the R package spatstat I'm plotting pooled pointwise envelopes of the function Jfox calculated for different point pattern in an hyperframe. The workflow is ...
2answers
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### spatstat::plot.envelope observed line longer than shading

Using the R package spatstat I'm plotting pooled pointwise envelopes of the function Jfox calculated for different point pattern in an hyperframe. The workflow is ...
0answers
17 views

### How to measure the effects of multiple shorter time-series on one longer time-series?

I have a question pertains to time-series analysis. For example, I have a time-series data about the downloads of an app for a month. And I want to know that the effects on the downloads time-series ...
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### Hawkes processes: interpretation of maximum likelihood estimates disagreeing with moment estimator estimates?

So, I have some data.. and a parameterized Hawkes process which I estimate parameters for via maximum likelihood... the residuals ( the compensator aka the dual-predictable projection) are good in ...
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196 views

### Distribution of distance to nearest (farthest) neighbour in normal data cloud

Here is an example of standard normal datasets (spherical, i.e. identity covariance matrices) in 1, 2, 3, 5, 10 dimensions, n=100 points. The picture shows observed ...
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574 views

### Mean Nearest Neighbor test vs Nearest Neighbor function envelope test?

I am analyzing a point pattern using G (nearest neighbor cumulative distribution) function, followed up by the envelope tests and in the same time using Nearest Neighbor Index test (Clark Evans test )...
1answer
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### Test for summary funtions: KS or envelope tests?

I want to study a point pattern using cumulative NND (Nearest Neighbor Distance) "G" function . The main task is to test H0: the point process is compatible with a null model (can be CSR (complete ...
0answers
147 views

### Extracting intervals out of an unevenly spaced time series

I am having a list of unevenly spaced data points - just occurrences, no values - and want to split them into intervals grouping occurrences, which are close together like so: Currently I am ...
1answer
109 views

### All-to-All distances for point pattern analysis

I am new to point pattern analysis. Trough my readings I haven't seen that any book would suggest to use All-to-All distances for point pattern analysis, but rather they talk about NND or other ...