Skip to main content

programming - FindFit and NMinimize to fit a parametric model (minimize the distance of two curves)


I am trying to find a fit to the cumulative distribution of a set of points using FindFit or NMinimize.


In particular, I would like to find the parameters of the cdf of the Beta Distribution that would minimize the uniform distance to the cumulative distribution of the above mentionned points.


So in particular, I am avoiding the use of NonLinearModelFit for reasons outlined here What is the difference between FindFit and NonlinearModelFit


However I get errors. I would appreciate a lot if someone could have a look at my code and let me know what am I missing.. (I tried a bunch of solutions neither works..)


So, here is the empirical cumulative probability function (in my problem it is a function derived from a non-parameteric kernel) but let us cook it up as a piecewise function:


 piece[x_] := Piecewise[{{x^3, 1 >= x >= 0}, {1, x > 1}}, 0]

Now I generate my "model" whose parameters I want to determine


funcr[al_?NumericQ, be_?NumericQ, x_?NumericQ] := 

CDF[BetaDistribution[al, be], x];

So I can define first a norm which I will be later minimizing with respect to parameters $al$ and $be$ of the beta distribution


 norm[al_, be_, x_] := Abs[funcr[al, be, x] - piece[x]];
max[al_, be_] := ArgMax[{norm[al, be, x], 0 <= x <= 1}, x]

And then I am trying to minimize this max function over all $\alpha$ and $\beta$ of the beta distribution (as given here by al_ and be_).


 NMinimize[{max[al, be], al >= 0, be >= 0}, {al, be}]

And at this stage I get the error:



 *The function value   
\Abs[-0.028069671808523725`+funcr[al,be,0.04573179628771076`]] is not \
a number at {x} = {0.04573179628771076`}. >>*

I know I am very pedestrian with my code, but I would really appreciate all your suggestions from which I can learn how to be a bit more sophisticated and especially correct....!



Answer



You could do for example:


int[al_?NumericQ, be_?NumericQ] := NIntegrate[(funcr[al, be, x] - piece[x])^2, {x, 0, 1}]
nm = NMinimize[{int[al, be], al >= 1, be >= 1}, {al, be}]
Plot[{piece@x, funcr[al, be, x] /. nm[[2]]}, {x, 0, 1},

PlotStyle -> {{Thickness[.01], Red}, {Dashed, Thickness[.01], Blue}}]

Mathematica graphics


Comments

Popular posts from this blog

plotting - How to draw lines between specified dots on ListPlot?

I would like to create a plot where I have unconnected dots and some connected. So far, I have figured out how to draw the dots. My code is the following: ListPlot[{{1, 1}, {2, 2}, {3, 3}, {4, 4}, {1, 4}, {2, 5}, {3, 6}, {4, 7}, {1, 7}, {2, 8}, {3, 9}, {4, 10}, {1, 10}, {2, 11}, {3, 12}, {4,13}, {2.5, 7}}, Ticks -> {{1, 2, 3, 4}, None}, AxesStyle -> Thin, TicksStyle -> Directive[Black, Bold, 12], Mesh -> Full] I have thought using ListLinePlot command, but I don't know how to specify to the command to draw only selected lines between the dots. Do have any suggestions/hints on how to do that? Thank you. Answer One possibility would be to use Epilog with Line : ListPlot[ {{1, 1}, {2, 2}, {3, 3}, {4, 4}, {1, 4}, {2, 5}, {3, 6}, {4, 7}, {1, 7}, {2, 8}, {3, 9}, {4, 10}, {1, 10}, {2, 11}, {3, 12}, {4, 13}, {2.5, 7}}, Ticks -> {{1, 2, 3, 4}, None}, AxesStyle -> Thin, TicksStyle -> Directive[Black, Bold, 12], Mesh -> Full, Epilog -> { Line[ ...

equation solving - Invert and fit implicitly defined curve

I need to fit an implicitly defined curve. I thought I could get some data out of Solve , and then using FindFit . Therefore, I would like to find the relation the parametric curve defined by $F(x,y)=0$: Solve[-(1/2) + 1/2 (0.41202 BesselK[0, 0.1 Sqrt[x^2 + y^2]] + (0.101483 x BesselK[1, 0.1 Sqrt[x^2 + y^2]])/Sqrt[x^2 + y^2]) == 0, y] But I can't get an output: Solve was unable to solve the system with inexact coefficients or the system obtained by direct rationalization of inexact numbers present in the system. Since many of the methods used by Solve require exact input, providing Solve with an exact version of the system may help. >> Edit: In particular, I would like to fit the data coming from the curve with the expression of another curve, and not with a function $f(x)$. In particular, since this clearly looks like a cardioid , I would like it to fit to something like it. What other strategies could I try?

dynamic - How can I make a clickable ArrayPlot that returns input?

I would like to create a dynamic ArrayPlot so that the rectangles, when clicked, provide the input. Can I use ArrayPlot for this? Or is there something else I should have to use? Answer ArrayPlot is much more than just a simple array like Grid : it represents a ranged 2D dataset, and its visualization can be finetuned by options like DataReversed and DataRange . These features make it quite complicated to reproduce the same layout and order with Grid . Here I offer AnnotatedArrayPlot which comes in handy when your dataset is more than just a flat 2D array. The dynamic interface allows highlighting individual cells and possibly interacting with them. AnnotatedArrayPlot works the same way as ArrayPlot and accepts the same options plus Enabled , HighlightCoordinates , HighlightStyle and HighlightElementFunction . data = {{Missing["HasSomeMoreData"], GrayLevel[ 1], {RGBColor[0, 1, 1], RGBColor[0, 0, 1], GrayLevel[1]}, RGBColor[0, 1, 0]}, {GrayLevel[0], GrayLevel...