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PointProcessFitTest—Wolfram Language Documentation

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BUILT-IN SYMBOL

PointProcessFitTest[pdata]

tests whether the point collection pdata could be modeled by a Poisson point process.

PointProcessFitTest[pdata,pproc]

tests whether the point collection could be modeled by the point process pproc.

Details and Options Examplesopen allclose all Basic Examples  (2)

Uniform point distribution on a disk:

The data came from a point process with homogeneous intensity:

Points distributed over a geographical region:

Estimated PoissonPointProcess:

Test the goodness of fit:

Scope  (10) Testing  (7)

Testing:

The -values are typically large when points are uniformly distributed:

The -values are typically small when there is spatial heterogeneity:

Perform a particular test for spatial randomness:

Using Automatic applies the "BesagL" test:

The property "AutomaticTest" can be used to determine which test was chosen:

Perform all tests appropriate to the data simultaneously:

Use the property "AllTests" to see which tests are available:

Create a HypothesisTestData object for repeated property extraction:

The properties available for extraction:

Extract some properties from the HypothesisTestData object:

The -value and test statistic from the "BesagL" test:

Extract any number of properties simultaneously:

The -value and test statistic from a "BesagL" test:

Reporting  (3)

Tabulate the results from a selection of tests:

A full table of all appropriate test results:

A table of selected test results:

Retrieve the entries from a test table for customized reporting:

The -values are above 0.05, so there is not enough evidence to reject at that level:

Tabulate -values for a test or group of tests:

The -value from the table:

A table of -values from all appropriate tests:

Options  (2) SignificanceLevel  (1)

The significance level is used for "TestConclusion" and "ShortTestConclusion":

The test conclusions may differ:

Full test conclusions:

MaxIterations  (1)

You can control the number of simulations with suboption MaxIterations:

Properties & Relations  (1) Neat Examples  (1)

Distribution of the "ChiSquare" test statistic under a null hypothesis:

Wolfram Research (2020), PointProcessFitTest, Wolfram Language function, https://reference.wolfram.com/language/ref/PointProcessFitTest.html. Text

Wolfram Research (2020), PointProcessFitTest, Wolfram Language function, https://reference.wolfram.com/language/ref/PointProcessFitTest.html.

CMS

Wolfram Language. 2020. "PointProcessFitTest." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/PointProcessFitTest.html.

APA

Wolfram Language. (2020). PointProcessFitTest. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/PointProcessFitTest.html

BibTeX

@misc{reference.wolfram_2025_pointprocessfittest, author="Wolfram Research", title="{PointProcessFitTest}", year="2020", howpublished="\url{https://reference.wolfram.com/language/ref/PointProcessFitTest.html}", note=[Accessed: 12-July-2025 ]}

BibLaTeX

@online{reference.wolfram_2025_pointprocessfittest, organization={Wolfram Research}, title={PointProcessFitTest}, year={2020}, url={https://reference.wolfram.com/language/ref/PointProcessFitTest.html}, note=[Accessed: 12-July-2025 ]}


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