Data provided by National Institute of Standards and Technology
Python scripts and Python+Qt graphical user interface for calculating Feldman-Cousins confidence intervals for low-count Poisson processes in the presence of a known background and for Gaussian processes with a physical lower limit of 0.
About this Dataset
Updated: 2024-02-22
Metadata Last Updated:
2022-08-19 00:00:00
Date Created:
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Data Provided by:
python
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| Title | FCpy: Feldman-Cousins Confidence Interval Calculator |
|---|---|
| Description | Python scripts and Python+Qt graphical user interface for calculating Feldman-Cousins confidence intervals for low-count Poisson processes in the presence of a known background and for Gaussian processes with a physical lower limit of 0. |
| Modified | 2022-08-19 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | Python , SIMS , Statistics , Mass Spectrometry , Confidence Interval , CI , Feldman , Cousins , Poisson , Gaussian |
{
"identifier": "ark:\/88434\/mds2-2755",
"accessLevel": "public",
"contactPoint": {
"hasEmail": "mailto:[email protected]",
"fn": "Evan Groopman"
},
"programCode": [
"006:045"
],
"@type": "dcat:Dataset",
"description": "Python scripts and Python+Qt graphical user interface for calculating Feldman-Cousins confidence intervals for low-count Poisson processes in the presence of a known background and for Gaussian processes with a physical lower limit of 0.",
"language": [
"en"
],
"title": "FCpy: Feldman-Cousins Confidence Interval Calculator",
"distribution": [
{
"downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2755\/FCpy.zip",
"description": "Python scripts and documentation for calculating Feldman-Cousins confidence intervals for low-count Poisson processes",
"mediaType": "application\/x-zip-compressed",
"title": "FCpy"
}
],
"license": "https:\/\/www.nist.gov\/open\/license",
"bureauCode": [
"006:55"
],
"rights": "NIST Software license applies",
"modified": "2022-08-19 00:00:00",
"publisher": {
"@type": "org:Organization",
"name": "National Institute of Standards and Technology"
},
"accrualPeriodicity": "R\/P1Y",
"theme": [
"Materials:Materials characterization",
"Mathematics and Statistics:Numerical methods and software",
"Physics:Nuclear physics"
],
"issued": "2022-12-01",
"keyword": [
"Python",
"SIMS",
"Statistics",
"Mass Spectrometry",
"Confidence Interval",
"CI",
"Feldman",
"Cousins",
"Poisson",
"Gaussian"
]
}
