# Questions tagged [regression]

Regression analysis is the process of measuring and establishing a relationship between a dependent variable and one or more independent variables.

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### Fitting Implicit Surfaces to Oriented Point Sets

I have a question regarding quadric fit to a set of points and corresponding normals (or equivalently, tangents). Fitting quadric surfaces to point data is well explored. Some works are as follows: ...
2answers
648 views

### Quickly finding rough lines in sets of points

In a particular class of detectors, our data comes out as pairs of points in two dimensions, and we want to string these points into lines. The data is noisy, and is binned in one direction but not ...
2answers
2k views

### Reporting curve-fit results in a scientific paper

(I hope this question fits this site; if not, accept my apologies). I ran a certain simulation, and got a time series y(t), t = 0, 1, ... 20. After trying some functions, I found that: ...
6answers
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2answers
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### Parameter Fitting: Need measure of data 'support' for a parameter solution

I am estimating parameters on a dataset that would, for the most part, result in a weakly constrained solution. The dataset however also contains a few more data points that make the solution well-...
1answer
175 views

### Recover curves from noisy collection of points

Background: I'm trying to make a system that tracks a number of bubbles in a video I'm implementing the bubble detection in the single image case using the Circular Hough Transform. Due to occlusion,...
0answers
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### Least-squares fit of explicit parabolic sheet to data points

For a given set of data points $$\{(x_i, y_i, z_i)\}$$ there exists some $$f_{ABC}(x,y)=Ax^2+Bxy+Cy^2$$ that minimizes $$\sum_i(f_{ABC}(x_i,y_i)-z_i)^2$$ $A$, $B$, and $C$ can be found quickly ...
0answers
1k views

### Polynomial Fitting with Least Squares using Numpy and Scipy

I am trying to fit data to a polynomial using Python - Numpy. The points, with lines sketched above them are as in the picture. I am trying to fit those points to a polynomial of 4. or 5. degree. ...
0answers
73 views

### Why not use this simpler variant of Stepwise Regression?

In stepwise regression, you step predictor by predictor, each time selecting the one with the greatest correlation with the measurement, subtracting greedily to leave a residual with no correlation to ...
0answers
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### Partitioning Data for Multiple Regression Lines

We're all familiar with traditional least-squares method for constructing a straight line through a set of data points. The question is: suppose I show you a scatter plot which clearly is suggestive ...
2answers
390 views

### What equation should I fit this set of data points to?

I have done an experiment Estimation of silver nitrate by potentiometric titration with standard KCl solution. A plot of $\dfrac{\Delta E}{\Delta V}$ versus Volume of KCl solution gives the ...
1answer
521 views

### Polynomial Regression using Semidefinite Programming

I'm trying to design the frequency response function for a low-pass filter. I need the function to be polynomial and to fulfill the following constraints: the coefficients must sum to 1, the function ...
2answers
48 views

### Fitting 2D mapping data from multiple measurements

Given a set of points in a plane, and series of measurements of the distances between those points, how would I go about generating a best-fit model of the position of the points? For example, given ...
1answer
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1answer
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### Curve fitting for oscillating data

This is my first question. I have the following data that I'd like to approximate as a parametric function: \begin{align} y = a + (bx_1 + cx_2 + dx_3 + ex_1x_2 + fx_1x_3 + gx_2x_3 + hx_1x_2x_3 + i)*(...
1answer
507 views

### Constrained linear least squares matrix equation

It has been a while since I have done linear least squares, so forgive the simple question, but here goes: I am attempting to find the best fit coefficients, $\{c_i\}$, of a linear combination of ...
1answer
69 views

### Correct weighting in least squares fitting

I am trying to fit some data points $d_i$ to a non-linear model function $m_i$, which depends on a number of fit parameters $f_k$ (I want to determine these) and also on some known, constant values \$...