Troubleshooting Ezyfit: Solving Fit Problems with NaN Data and Multiple Datasets

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In summary, the conversation is about a problem with NaN entities in a dataset and difficulty in finding a fit using the Ezyfit tool. The person has tried using Excel as well, but still cannot get a fit for both datasets. They are seeking help with this issue.
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euhre
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Hello again,

Part of the problem is solved. There were NaN entities in the dataset. I removed those, now a fit can be made, but still, only through 1 dataset (see figure). How to put the fit through both??

Grz. Fr@nk

Hello everybody,

I have a very large set of datapoints (about 500). I try showfit with Ezyfit tool, but it doesn't find a fit. I tried it with Excel, and this works. When I use the coefficients from Excel as first guess for Ezyfit, it plots the line but no information about R^2 is shown. What might be the problem... Additional problem is that the fit is only drawn for 1 dataset instead of the 2 together.

Hope somebody can help me

Grz Fr@nk
 

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Related to Troubleshooting Ezyfit: Solving Fit Problems with NaN Data and Multiple Datasets

1. What is Ezyfit?

Ezyfit is a software package designed for curve fitting and data analysis. It allows users to easily fit data to mathematical models and obtain optimized parameters.

2. How does Ezyfit handle NaN data?

Ezyfit has a built-in function to automatically remove NaN (Not a Number) data from datasets. This ensures that only valid data points are used in the curve fitting process.

3. Can Ezyfit handle multiple datasets?

Yes, Ezyfit has the capability to handle multiple datasets simultaneously. This allows for comparison and analysis of different datasets using the same mathematical model.

4. What are the common fit problems that Ezyfit can solve?

Ezyfit can solve a variety of fit problems, including overfitting, underfitting, and convergence issues. It also has options to adjust fitting parameters and constraints to improve the fit quality.

5. Is Ezyfit suitable for all types of data?

Ezyfit is primarily designed for scientific and engineering data, but it can also be used for other types of data as long as they can be represented by a mathematical model.

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