0
votes
0answers
21 views

numerical (script) fit of function with 2 arguments

I would like to find the least-square fit for a 1D-function that takes two arguments. m(x,y) = d * (x-x0)^2 / (y-y0)^2 I would like to write a c++ routine to ...
4
votes
2answers
68 views

Rewriting the matrix equation $AX = YB$ as $Y = CX$?

Is it possible in general, if $A,B,C,X,Y$ are square and of the same dimensions? If so, does it generalize to non-square matrices (using a pseudoinverse)? I'm doing some curve fitting in which I have ...
2
votes
1answer
46 views

Trigonometric regression

What methods are performed for regression with trigonometric functions? E.g. : Sequence: $$-1, 0, 1, -1, 0, 1, \text{.....}$$ Regression: ...
1
vote
1answer
41 views
2
votes
1answer
204 views

What is the difference between Curve Fitting and Regression(Machine Learning)?

I know that Machine Learning regression algorithms try to find the function of the data. That is, if we have 1000 data points (x,y), to find a general continuous function that follows the trends of ...
0
votes
0answers
128 views

Is my form of Lorentz and Gaussian equations suitable for curve fitting?

I am attempting to curve fit gas chromatography spectra. These spectra can be Lorentz or Gaussian or a combination of both. I am using the following code for these equations. ...
0
votes
1answer
142 views

Determining slope of line relative to a maximum

In the following scientific report (Seismic Q estimation), a mathematical procedure of linear curve-fitting is described in words. The authors state: The stratigraphic effects are minimized by ...
2
votes
1answer
60 views

Possibility of Unboundedness in Least Squares Minimization

Suppose we have the quadratic minimization problem \begin{equation} \min_x \frac{1}{2} x^TPx + q^Tx +r \end{equation} We know that when $P$ is symmetric positive semi-definite, but the optimality ...
4
votes
2answers
101 views

Linear regression where undershooting isn't as bad as overshooting

Given a set of points $(x_i, y_i)$, least-squares linear regression finds the linear function $L$ such that $$\sum \varepsilon(y_i, L(x_i))$$ is minimized, where $\varepsilon(y, y') = (y-y')^2$ is the ...
2
votes
0answers
331 views

Logistic regression algorithm in Casio and Texas Instruments calculators

When using logistic regression on a Casio or Texas Instruments calculator, the output is of the form $$f(x) = \frac{c}{1+ae^{-bx}} $$ The problem I have (when teaching in a class where both types of ...
4
votes
2answers
683 views

How does one fit the curve $y = ae^{bx} + c$?

How does one fit the curve $y = ae^{bx} + c$? The method of taking logarithms of both sides does not simplify to allow linear regression. I can take the three equations derived from setting the ...
6
votes
1answer
95 views

Formula for straight part of a slightly bumpy line

Given a straight line that deviates from the horizontal by at most 15 degrees. On this straight line there are bumps on top at random places on the line. The combined width of the bumps is at most ...
1
vote
5answers
511 views

Find square root approximation function (tool)

first I have to apologize for any uncorrect naming or categorisation of my question, as I am an electrical engineer rather than a mathematican. I try to find a simple solution for my problem: I have ...
0
votes
1answer
347 views

Strange behaviour with ode45 in matlab, probably some numerical error.

I'm having a problem with a parameter estimation in a non-linear model. I think the culprit is that ode45 (an ode solver in matlab) is not properly solving my ode. It's the in red highlighted part, ...
1
vote
1answer
395 views

Fitting a sine function to data

I have a sequence of $n$ points $(x_i,y_i)$, for $i=1,\dots,n$. I would like to find the function, of the form $y=V\sin(x+\phi)$, which best fits the points. Which numerical method could I use? I have ...
1
vote
1answer
677 views

Simple non linear fitting question(Least Squares Fitting--Exponential) [duplicate]

Possible Duplicate: easy to implement method to fit a power function (regression) I have the following simple function: $h = cV^n$ h and V being the variables and $c$ and $n$ are ...