https://nirpyresearch.com Statistical learning and chemometrics in Python Fri, 25 Sep 2026 23:03:23 +0000 en-AU hourly 1 https://wordpress.org/?v=7.1.3 https://nirpyresearch.com/wp-content/uploads/2019/07/apple-icon-152x152-1-150x150.png https://nirpyresearch.com 32 32 https://nirpyresearch.com/optimising-regularisation-parameters-whittaker-smoothing/ Sun, 13 Sep 2026 02:53:46 +0000 https://nirpyresearch.com/?p=3695 Whittaker smoothing (aka Tikhonov regularisation) requires the estimation the regularisation parameter. In this tutorial we discuss and compare two approaches.]]> https://nirpyresearch.com/whittaker-smoothing/ Fri, 21 Aug 2026 08:24:09 +0000 https://nirpyresearch.com/?p=3646 The "perfect smoother". Step-by-step explanation and Python script to smooth spectra using Tikhonov regularisation.]]> https://nirpyresearch.com/robust-msc/ Sun, 05 Oct 2025 04:07:20 +0000 https://nirpyresearch.com/?p=3384 Robust MSC is an implementation of multiplicative scatter correction that is better suited at handling outliers in the original spectra.]]> https://nirpyresearch.com/include-msc-custom-pipeline-scikit-learn/ Sat, 07 Dec 2024 07:51:01 +0000 https://nirpyresearch.com/?p=3334 Learn how to include Multiplicative scatter correction in a custom pipeline using scikit-learn.]]> https://nirpyresearch.com/generate-synthetic-mixtures-from-pure-spectra/ Fri, 15 Nov 2024 02:27:54 +0000 https://nirpyresearch.com/?p=3293 A Python script to generate random synthetic mixtures from pure spectra from a database. This post can be used as a tutorial to generate datasets for Multivariate Curve Resolution. ]]> https://nirpyresearch.com/diagnostic-plots-for-linear-regression/ Sat, 05 Oct 2024 08:36:31 +0000 https://nirpyresearch.com/?p=3220 A short survey of diagnostic plots, as tools to dig deeper on the assumptions behind a regression model.]]> https://nirpyresearch.com/genetic-algorithm-wavelength-selection-numpy/ Sat, 22 Jun 2024 09:48:43 +0000 https://nirpyresearch.com/?p=3173 A implementation of a genetic algorithm for wavelength selection using basic Numpy functions.]]>