# Tagged Questions

Questions on the use of Mathematica to construct models for approximating empirical data. (FindFit[], Fit[], LinearModelFit[], NonlinearModelFit[], etc.)

4answers
2k views

### Using FindFit to fit $a\,b^t$: how to avoid introducing complex numbers?

I'd like to find a model $f(t)=a\,b^t$ which matches the following data ...
3answers
763 views

### Mathematica envelope for the bottom of a plot, a generic function

I have the following set-up: xaxis = Table[x, {x, 0, 10, 0.01}]; yaxis = Table [Sin[x] + Abs[RandomReal[{-1, 1}]], {x, 0, 10, 0.01}]; ListLinePlot[Transpose[{ xaxis, yaxis}]] My ...
4answers
2k views

### Problem with NonlinearModelFit

I'm having trouble with a non-linear fit: fit = NonlinearModelFit[data, y0 + A Sin[\[Pi] (x - xc)/w], {y0, xc, A, w}, x] where ...
3answers
803 views

### Fitting fractional complex data with NonlinearModelfit

I've difficulites with the NonlinearModelFit function. In principle Mathematica should be able to deal with complex data. E.g. if I define the following table ...
6answers
1k views

### How to determine the center and radius of a circle given three points in 3D?

I was wondering if anyone could give me a hand with this problem I have. I have six points on a plane, and I am trying to determine if they form a circle or not. I know that any three points in 2D ...
3answers
438 views

### Ηow to create an interpolated CDF from its samples?

I want to use a distribution I have only aggregate statistics on, namely its CDF sampled at certain points. I would like to keep it "nonparametric" (remain noncommittal on the parametric form), but I ...
3answers
838 views

### Data fitting with Image processing feature detection

I have some 2D data that once plotted looks like the following ...
2answers
323 views

### Is it possible to use the LevenbergMarquardt algorithm for fitting a black-box residual function?

I have a black-box multiargument multiparametric function of the type SRD[dataPoint_List,params_List] which accepts experimental data along with the parameters of ...
4answers
818 views

### How to visualize 3D fit

I have a data set of x,y,z values and I fit a function of x,y to the data. This works, but I can't come up with a nice way to ...
4answers
2k views

### Simultaneously fitting multiple datasets

What is the proposed approach if one wants to simultaneously fit multiple functions to multiple datasets with shared parameters? As an example consider the following case: We have to measurements of ...
5answers
2k views

### Estimate error on slope of linear regression given data with associated uncertainty

Given a set of data, is it possible to create a linear regression which has a slope error that takes into account the uncertainty of the data? This is for a high school class, and so the normal ...
4answers
603 views

### Mathematica Implementations of the Random Forest algorithm

Is anyone aware of Mathematica use/implementation of Random Forest algorithm?
3answers
678 views

### How to use FindFit to fit an implicit function?

Now I am trying to fit some data with a implicit model function. Firstly, I tried a toy example. Toy example with input and output ...
1answer
388 views

### How do I find the best parameter to fit my data if the model is a interpolating function?

Hi I have a question regarding to find the best parameters for my model to fit my data. I have 3 ordinary equation, and I now just picked some parameters (...
0answers
191 views

### Mathematica vs Sigmaplot (Non LinearModelFit)

I asked a question in a previous post that was closed because "The title of the question is not correct and the issue here is too trivial to help anyone later". NonLinearModelFit It's possible ...
5answers
411 views

### How to plot Fit functions?

If I do something like this f[x_]:=x^2 Plot[f[x],{x,1,10}] Mathematica plots the function $f(x)=x^2$, as expected. However, ...
0answers
74 views

### Is it possible to marginalize one or several parameters obtained from fitting procedure?

Statistical model analysis package has a few fitting functions. Their arguments are data points, fitting model and parameters in the fit. The result is a set of best values for parameters, which ...
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