Min.Version: 2023 (10.0) Updated on: 11/4/2022

Fit a series of pulses.

Min.Version: 2022b (9.95) Updated on: 10/28/2022

Perform neural network fitting using Python.

Min.Version: 2019b (9.65) Updated on: 8/17/2022

Perform batch fitting fast

Min.Version: 2019b (9.65) Updated on: 6/27/2022

Fit ordinary differential equation

Min.Version: 2019 (9.6) Updated on: 6/21/2022

Offer an intuitive and interactive interface to perform peak analysis.

Min.Version: 2020 (9.7) Updated on: 6/15/2022

Fit data with neural network.

Min.Version: 2022b (9.95) Updated on: 6/8/2022

Analyze radiometric geochronological data.

Min.Version: 2017 (9.4) Updated on: 5/11/2022

Perform regression to study the relationship between a response variable and categorical or continuous independent variables.

Min.Version: 2019 (9.6) Updated on: 4/25/2022

Perform global fit and share parameters for different functions.

Min.Version: 2019b (9.65) Updated on: 3/21/2022

Explore the relation between continuous or categorical independent variables and specified quantiles of a dependent variable.

Min.Version: 2018b (9.55) Updated on: 1/4/2022

Fit and rank multiple functions to identify best fitting model.

Min.Version: 2019 (9.6) Updated on: 12/17/2021

A simplified tool to perform curve fitting.

Min.Version: 2018b (9.55) Updated on: 12/17/2021

Perform convolution of the fitting function with the instrument response while performing the fitting.

Min.Version: 2016 (9.3) Updated on: 11/22/2021

Compare parameters across multiple datasets, or compare multiple datasets using a nonlinear model.

Min.Version: 2020 (9.7) Updated on: 11/17/2021

Perform 2d peak fitting and integration for each peak.

Min.Version: 2018b (9.55) Updated on: 11/17/2021

Perform fitting on all datasets in a worksheet sequentially.

Min.Version: 2019 (9.6) Updated on: 11/17/2021

Perform fitting by combining two or more existing fitting functions

Min.Version: 2020b (9.75) Updated on: 7/1/2021

Fit a linear model with fixed effects and random effects.

Min.Version: 2019 (9.6) Updated on: 6/10/2021

Let Origin user search, find and add fitting functions to Origin.

Min.Version: 2016 (9.3) Updated on: 4/21/2021

Compare datasets using a linear model, or compare intercept and slope.

Min.Version: 2021 (9.8) Updated on: 4/6/2021

Perform bayesian ridge regression with Python.

Min.Version: 2021 (9.8) Updated on: 3/16/2021

Rank multiple fitting functions by their fit reports.

Min.Version: 2019 (9.6) Updated on: 12/21/2020

Test for a specific value of a fit parameter

Min.Version: 2020b (9.75) Updated on: 6/9/2020

Help to transform raw data related to adsorption isotherm into a linear dataset then perform linear fitting.

Min.Version: 2020b (9.75) Updated on: 4/27/2020

Fit a standard curve and interpolate x values.

Min.Version: 2020b (9.75) Updated on: 4/27/2020

Linear regression with marginal distribution

Min.Version: 2017 (9.4) Updated on: 10/10/2019

Perform multi-peak fitting and integration of cyclic data.

Min.Version: 2018 (9.5) Updated on: 8/5/2019

Fit two or three segments of a data plot with same or different fitting function.

Min.Version: 2018 (9.5) Updated on: 8/2/2019

View and manage a list of operations (analyses, etc) in the current project.

Min.Version: 2018b (9.55) Updated on: 3/14/2019

Pack project file including fitting functions and templates

Min.Version: 2018b (9.55) Updated on: 6/24/2018

Determine the coefficients of Chebyshev polynomials of the first kind.

Min.Version: 2018 (9.5) Updated on: 12/18/2017

Fit multiple peaks in multiple datasets with parameter sharing.

Min.Version: 2018 (9.5) Updated on: 12/8/2017

Fit enzyme kinetics data and rank models.

Min.Version: 2018 (9.5) Updated on: 9/26/2017

Perform multiple linear regression for spectra.

Min.Version: 2017 (9.4) SR1 Updated on: 5/8/2017

Perform constrained multiple regression and solve constrained linear least-squares problems (PRO Only).

Min.Version: 2017 (9.4) Updated on: 1/20/2017

Perform Weibull fit using rank regression on X

Min.Version: 2016 (9.3) Updated on: 2/25/2016

Fit XYZ data with polynomial equations of specified/maximum degree in X and Y, and rank equations to determine best fit (PRO Only).