How to Apply Curve Fitting Algorithms for Magnetization Analysis in Origin 7?

AI Thread Summary
The discussion centers on using a curve fitting algorithm to analyze magnetization (M) versus applied field (H) data, with a focus on fitting a log-normal distribution to the model parameters. The user is working with the Langevin function and seeks guidance on implementing this in Origin 7 software. Two primary methods for curve fitting are suggested: least squares fitting, which minimizes the squared differences between the model and data, and maximum likelihood estimation (MLE), which maximizes the likelihood of the observed data. The importance of specifying the log-normal distribution function and data points for fitting is emphasized. Users are encouraged to consult the Origin 7 manual and explore online resources for further assistance in applying these curve fitting techniques.
mhill
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hi, there my question is let's suppose we have the magnetization (M) versus the applied field (H) as

M(H,T)= \sum _{n=1}^{N} W(x_i ) (x_i ) Lang (H.A.x_{i}/T)

here 'A' is a constant 'T' is the temperature of system Lang(x) is the Langevin function coth(x)-1/x ,

My problem is how to use a curve fitting algorithm to solve the problem ,i am working under the assumption that W(x_i) i=1,2,3,...,N is a log normal distribution depending only on the value x_i

my curve fitting program is just 'Origin 7' i need the algorithm to curve-fitting to a certain given distribution W(x) thanks.

P.D in case you see this post in another forum, sorry i made a mistake erase this post and keep only the one made in the 'programming' forum.
 
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Hello,

Thank you for your question. It seems like you are trying to fit a log normal distribution to a set of data points in order to determine the parameters of your model. There are a few different approaches you could take to solve this problem using a curve fitting algorithm.

One approach is to use a least squares fitting method, which involves minimizing the sum of the squared differences between your model and the data points. This can be done using a built-in function in Origin 7 or by writing your own code to perform the fitting.

Another approach is to use a maximum likelihood estimation (MLE) method, which involves finding the parameters that maximize the likelihood of the observed data. This can also be done using a built-in function or by writing your own code.

In either case, you will need to specify the log normal distribution function and the data points you are trying to fit. The algorithm will then calculate the best-fit parameters for the distribution.

I suggest consulting the Origin 7 user manual or seeking help from their support team for more specific instructions on how to perform curve fitting using their software. Additionally, there are many online resources and tutorials available for using curve fitting algorithms in general, so you may find it helpful to do some additional research on this topic.

I hope this helps. Best of luck with your research.

 
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