A reliable and reproducible way of fitting non-linear regression over levels of a factor in R
-
Updated
Dec 8, 2017 - R
A reliable and reproducible way of fitting non-linear regression over levels of a factor in R
Course work of Multivariate data analysis CH5440
Robust Regression for arbitrary non-linear functions
solving nonlinear scoring problems where linear regression doesn't fit well using techniques like Generalized Additive Models (GAM) and Support Vector Regression (SVR).
Hierarchical dose-response models in R
Modelos de Regressão Não Linear
Edison을 통한 비선형 약동학 회귀 분석과 simulation (Gabrielsson - PK02, PK08, PK09) https://cmed.edison.re.kr/scienceappstore
Code and Simulations using Bayesian Approximate Kernel Regression (BAKR)
Pulses analysis using mysql server for data saving
A Chinese guide book for learning Tensorflow from a starter.
Project on Compartment model.
Nonlinear regression using to estimate kinetics constants of DNA promoter opening and escape during transcription initiation complex assembled between Lambda PR promoter and E. coli RNA polymerase.
A malloc-free Levenberg-Marquardt optimizer for nonlinear least squares regression
CSE 569, Fall 2019 Fundamentals of Statistical Learning Course at ASU
Nonlinear regression in Julia
Nonlinear Regression Models
Regularized Levenberg-Marquardt algorithm for nonlinear regression on small size datasets
GMPE-estimation implements a one-stage estimation algorithm to estimate ground-motion prediction equations (GMPE) with spatial correlation. It also quantifies the uncertainty of spatial correlation and intensity measure predictions.
TensorFit is an open source package for curve fitting.
Add a description, image, and links to the nonlinear-regression topic page so that developers can more easily learn about it.
To associate your repository with the nonlinear-regression topic, visit your repo's landing page and select "manage topics."