Skip to main content

Package that implements the isotonic estimator for Wicksell's problem.

Project description

This package implements the isotonic estimator for Wicksell's problem given in the paper Adaptive and Efficient Isotonic Estimation in Wicksell's Problem.

How to use the package? After installing the package via the usual command line pip install, the user user can import the package using the lines of code:

from isotonic_estimator_lib import isotonic_estimator

then, having a vector of observed samples Z, the user can obtain the isotonic estimator together with its plot by running:

max_xs = max(Z)
res = isotonic_estimator.estimator(max_xs,Z)

where max_xs is needed for plotting purposes only. The resulting estimated cdf F of the hidden radii distribution is now stored into res. The resulting plot should look as follows:

We have also designed a test application in tkinter which is included in the package and where the user can visualize the performance of the isotonic estimator. After running the following code:

from isotonic_estimator_lib import tester_quality
tester_quality.tester()

a pop-up window will open asking to input a test hidden cdf F which can be chosen between the following set of distributions: "gamma, chi, betaprime, pareto, lognormal, truncnorm, arcsine, fatiguelife, weibull". The input is case sensitive. If the user gives non acceptable inputs, the tester will automatically produce an error. The suggested number of samples is 200, and it is not recommended to choose a value higher than 1000. The tester will produce some plots that illustrate the performance of the isotonic estimator. The resulting plot should look like this:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

isotonic_estimator_lib-0.0.7.tar.gz (7.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

isotonic_estimator_lib-0.0.7-py3-none-any.whl (8.7 kB view details)

Uploaded Python 3

File details

Details for the file isotonic_estimator_lib-0.0.7.tar.gz.

File metadata

  • Download URL: isotonic_estimator_lib-0.0.7.tar.gz
  • Upload date:
  • Size: 7.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.6

File hashes

Hashes for isotonic_estimator_lib-0.0.7.tar.gz
Algorithm Hash digest
SHA256 cea41e02b417c571cd716d2eb584a02ac3de43b0063b2ffddd1ddf932e3abb66
MD5 49e2a7dd3dc0aafa5b167cf21176fa1f
BLAKE2b-256 d4a2f2c48231e3f19c384a5a2c2f0abf2bd3d099f6a4d5f7f2a0f0f11d3e03bb

See more details on using hashes here.

File details

Details for the file isotonic_estimator_lib-0.0.7-py3-none-any.whl.

File metadata

File hashes

Hashes for isotonic_estimator_lib-0.0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 b223a576cbb0975830aa0042fe726f0016b1376ae7e98a452595509f7af4e697
MD5 4596258a4a28bd1ca83ec8a9833c7c90
BLAKE2b-256 e6cbcb7133010f294aa17013a8f5146214abde81918742bdee509726a3437f94

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page