tl;dr: I'm wondering if there's a name for the family of methods shown below, whether or not my method is known, and an analysis on how well it performs.

Try some code online, close the tabs and see the output at the bottom.

Recently I've been looking into root-finding methods for continuous functions with odd order roots (i.e. there exists $[a,b]$ s.t. $f(a)f(b)<0$) that work by repeatedly reducing the interval over which the root is in. I've found that generally the methods take the form of

$$\hat c_k=\frac{a_kf(b_k)-b_kf(a_k)}{f(b_k)-f(a_k)}$$ $$c_k=\begin{cases}\hat c_k,&f(\hat c_k)f(c_{k-1})<0\\\dfrac{m_ka_kf(b_k)-b_kf(a_k)}{m_kf(b_k)-f(a_k)},&f(\hat c_k)f(c_{k-1})>0\land f(\hat c_k)f(b_k)>0\\\dfrac{a_kf(b_k)-n_kb_kf(a_k)}{f(b_k)-n_kf(a_k)},&f(\hat c_k)f(c_{k-1})>0\land f(\hat c_k)f(b_k)<0\end{cases}$$ $$[a_{k+1},b_{k+1}]=\begin{cases}[a_k,c_k],&f(c_k)f(b_k)>0\\ [c_k,b_k],&f(c_k)f(b_k)<0\end{cases}$$

where $m_k,n_k\in(0,1]$ are weights used to push the next $c_k$ towards the bound that isn't changing.

The case of $m_k=n_k=1$ is simply the false position/reguli falsi method and the case of $m_k=n_k=\frac12$ is the Illinois method, to name the simplest ones. There are some others but I've noticed that these methods do not seem to perform well when $f(b_k)/f(a_k)$ is very large or very small, in which case they may simply fail to create a sufficient weight to make the bounds move in fast enough.

To compensate I came up with a modification of the Illinois method:

$$c_k=\frac{a_kfb_k-b_kfa_k}{fb_k-fa_k}$$ $$[a_{k+1},b_{k+1}]=\begin{cases}[a_k,c_k],&f(c_k)fb_k>0\\ [c_k,b_k],&f(c_k)fb_k<0\end{cases}$$ $$fa_{k+1}=\begin{cases}fa_k,&a_{k+1}=a_k\ne a_{k-1},\\fa_k/2,&a_{k+1}=a_k=a_{k-1}\\f(c_k),&a_{k+1}\ne a_k\end{cases}$$ $$fb_{k+1}=\begin{cases}fb_k,&b_{k+1}=b_k\ne b_{k-1},\\fb_k/2,&b_{k+1}=b_k=b_{k-1}\\f(c_k),&b_{k+1}\ne b_k\end{cases}$$

which functions more or less like the Illinois method except $m_k$ and $n_k$ repeatedly halve if we're still updating only one bound.


enter image description here

Intuitively this corresponds to something along the lines of repeatedly increasing the rate at which the approximated root increases if we repeatedly underapproximate or repeatedly increasing the rate at which the approximated root decreases if we repeatedly overapproximate.

Using functions that should perform very poorly with secant-like methods such as $f(x)=x^{10}-0.1$ with $[a_0,b_0]=[0,3]$, it seems the worst case scenario is about as bad as bisection.

The only other such method I've found that seemed to work reasonably as well as this for extreme cases like $x^{10}-0.1$ with $[0,3]$ was a combination of false position + bisection, using bisection instead of weights. In less extreme cases, this out-performed the false position + bisection and worked similarly to other methods such as the Illinois and Adam-Björck methods.

Here are my questions:

  1. What are these kinds of methods called? I'm having a little difficulty researching them.

  2. Is my method known?

  3. What is the order of convergence? I'd guess somewhere between $\sqrt2$ (Illinois) and $2$ (best case like secant and Newton's methods).

  • $\begingroup$ 2 downvotes seems more than coincidence, I wonder what the reason for them is. $\endgroup$ Feb 18, 2020 at 22:29
  • $\begingroup$ Welcome to the club of victims of mysterious downvotes ! and +1 for a good question. $\endgroup$ Feb 19, 2020 at 6:32
  • $\begingroup$ How do I interpret $fa_k$? Is it just $f(a_k)$? $\endgroup$ Feb 21, 2020 at 14:38
  • $\begingroup$ @CarlChristian It is initialized to $f(a_k)$ when $a_k\ne a_{k-1}$. After that it eventually becomes $fa_{k-1}/2$. See the right side of the graphical example. $\endgroup$ Feb 21, 2020 at 15:57
  • $\begingroup$ Ah, thank you very much. It makes sense now. I will myself write fa as a variable when programming and use it to save $f(a)$. $\endgroup$ Feb 21, 2020 at 16:27

1 Answer 1


As far as I understand, continuing the halving as long as necessary is the Illinois variant of regula falsi. It is worth its own name because it has a very short implementation using an active-point-counter-point strategy, that is, the order $a_k<b_k$ is given up, $a_k$ is always the last computed midpoint, the "active" point of the iteration, and $b_k$ the "counter" point of opposing function value sign.

def illinois(f,a,b, eps):
    '''regula falsi resp. false postion method with
        the Illinois anti-stalling variation'''
    fa = f(a);
    fb = f(b);
    if abs(fa)>abs(fb): a,fa,b,fb = b,fb,a,fa
    while abs(b-a) > eps:
        c = a - (fa*(b-a))/(fb-fa);
        fc = f(c);
        print(f"c: {c:12.9f}->{fc:12.6g}   a:{a:12.9f}->{fa:12.6g}   b:{b:12.9f}->{fb:12.6g}")
        # current c moves to active a, ideally in counter position, so a moves to b
        if fa*fc <= 0:
            b = a; fb = fa; 
            # if stall, increase the (relative) weight of b
            fb *= 0.5
        a = c; fa = fc; 
    return a, fa

In practice in a situation of simple roots one mostly encounters one halving step, so the difference is not that grave. It then looks like two Illinois steps are equivalent to one secant step, giving a convergence rate somewhere around $1.3$

c:  0.212401106->    0.967945   a: 0.000000000->           1   b: 2.000000000->    -8.41615
c:  0.546692376->    0.690857   a: 0.212401106->    0.967945   b: 2.000000000->    -4.20807
c:  0.905928986->   -0.126548   a: 0.546692376->    0.690857   b: 2.000000000->    -2.10404
c:  0.850313226->   0.0449436   a: 0.905928986->   -0.126548   b: 0.546692376->    0.690857
c:  0.864888728->  0.00175991   a: 0.850313226->   0.0449436   b: 0.905928986->   -0.126548
c:  0.865999339-> -0.00158121   a: 0.864888728->  0.00175991   b: 0.905928986->  -0.0632739
c:  0.865473735-> 8.98005e-07   a: 0.865999339-> -0.00158121   b: 0.864888728->  0.00175991
c:  0.865474033-> 4.57771e-10   a: 0.865473735-> 8.98005e-07   b: 0.865999339-> -0.00158121
c:  0.865474033->-4.57304e-10   a: 0.865474033-> 4.57771e-10   b: 0.865999339->-0.000790605
returned value (0.8654740332536166, -4.573044165567808e-10)

enter image description here enter image description here

One can experiment in replacing the halving of the function value with an Aitken delta-squared step, as the stalling of the counter point leads to a geometric progression in the active point, it works well but does not have such a nice code. Here 3 steps combine to a third-order step (the sequence $ϵ,-ϵ,ϵ^2,ϵ^3,-ϵ^3$ with $ϵ\approx10^{-3}$ is visible in the above sequence of $f(c_k)$), which again gives an average rate of convergence of $\sqrt[3]3=1.44225$.

If one goes to the effort of more complex algorithms and code, the Dekker fzeroin method of combining a mostly secant iteration with a bracketing interval works overall better, giving a rate of convergence that is usually close to the rate $1.62$ of the secant method.

  • 1
    $\begingroup$ Do you have a reference for the Illinois method using repeated halving? From what I saw, it was only halving once at most. Also in all honesty, I'm a bit shaky on how to extract the order of convergence rigorously here. According to Wikipedia, the order should be $\sqrt2\simeq1.44$. $\endgroup$ Feb 19, 2020 at 13:08
  • $\begingroup$ Googling "active point counter point root finding" does not seem to turn up well, though I see this sort of behavior occurs with the Brent-Dekker method. You mention dropping the ordering $a_k<b_k$, but it seems to me that the Brent-Dekker method still keeps that, at least according to Wikipedia. $\endgroup$ Feb 19, 2020 at 13:22
  • 1
    $\begingroup$ @SimplyBeautifulArt The german wikipedia page was for a long time the only one that had the anti-stalling variants, and there one also has the repeated nature of the function value modification directly in the description, there one also has the active-counter strategy (needlessly recursive instead of iterative) without naming it so. $\endgroup$ Feb 19, 2020 at 13:58
  • 1
    $\begingroup$ Recently I've been researching a lot about bracketing methods such as the Illinois variant, and I was wondering if you'd be interested in chatting with me in my chatroom some time about them. $\endgroup$ Sep 12, 2020 at 2:54
  • 2
    $\begingroup$ Also possibly of interest to you, I have a proof that the Illinois method actually has an order of convergence of $\sqrt[3]3$, which is marginally better than Newton's method actually. You can numerically test the claims by trying the Illinois method to high precisions. $\endgroup$ Sep 12, 2020 at 3:57

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