<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>NLLS on Ned Charles's Website</title><link>https://nedcharles.com/tags/nlls/</link><description>Recent content in NLLS on Ned Charles's Website</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 15 Apr 2020 08:00:00 -0600</lastBuildDate><atom:link href="https://nedcharles.com/tags/nlls/index.xml" rel="self" type="application/rss+xml"/><item><title>Using Python Multiprocessing with NLLS Regression</title><link>https://nedcharles.com/articles/using_python_multiprocessing_with_nlls_regression/</link><pubDate>Wed, 15 Apr 2020 08:00:00 -0600</pubDate><guid>https://nedcharles.com/articles/using_python_multiprocessing_with_nlls_regression/</guid><description>A comparison of Nonlinear Least Squares Regression fitting on simulated data in Python, using the multiprocessing module versus a standard for loop</description></item><item><title>Nonlinear Least Squares Regression for Python</title><link>https://nedcharles.com/articles/nonlinear_least_squares_regression_for_python/</link><pubDate>Tue, 25 Feb 2020 12:00:00 -0600</pubDate><guid>https://nedcharles.com/articles/nonlinear_least_squares_regression_for_python/</guid><description>A walkthrough of some options for Nonlinear Least Squares Regression fitting in Python, including SciPy&amp;rsquo;s curve_fit and least_squares, along with the module LMFit</description></item><item><title>Part 4: Model Selection</title><link>https://nedcharles.com/articles/model_selection/</link><pubDate>Sun, 17 Sep 2017 12:00:00 -0600</pubDate><guid>https://nedcharles.com/articles/model_selection/</guid><description>This post investigates some common model selection methods, and does a detailed analysis of Akaike&amp;rsquo;s Information Criterion (AIC) and how it performs on some diffusion MRI models.</description></item><item><title>Part 3: Bootstrap, Graphical Analysis, and Kurtosis Model</title><link>https://nedcharles.com/articles/bootstrap_kurtosis/</link><pubDate>Sun, 13 Aug 2017 12:00:00 -0600</pubDate><guid>https://nedcharles.com/articles/bootstrap_kurtosis/</guid><description>This post looks at the statistical bootstrap as a method to diagnose ill-conditioning, graphical analysis of regression fitting, and examines the kurtosis Diffusion MRI model.</description></item><item><title>Part 2: The Biexponential Model and Ill-Conditioning</title><link>https://nedcharles.com/articles/biexponential_model/</link><pubDate>Sun, 30 Jul 2017 12:00:00 -0600</pubDate><guid>https://nedcharles.com/articles/biexponential_model/</guid><description>An investigation on the biexponential model used with diffusion MRI and how it can exhibit large uncertainty in its parameter estimates</description></item><item><title>Part 1: My PhD Thesis Introduction</title><link>https://nedcharles.com/articles/thesis_intro/</link><pubDate>Sun, 28 May 2017 12:00:00 -0600</pubDate><guid>https://nedcharles.com/articles/thesis_intro/</guid><description>A blog post about the statistical modelling work I did during my PhD</description></item><item><title>Nonlinear Regression Primer using MATLAB</title><link>https://nedcharles.com/articles/nonlinear_regression/</link><pubDate>Mon, 05 Sep 2016 06:00:00 -0600</pubDate><guid>https://nedcharles.com/articles/nonlinear_regression/</guid><description>A primer on how to use Nonlinear Regression with MATLAB</description></item></channel></rss>