A Halley-Aitken-type method for approximating the solutions of scalar equations

Abstract

We are concerned with the approximation of the solution of scalar equations by Halley-Aitken method. We obtain local convergence result.

Authors

Ion Păvăloiu
(Tiberiu Popoviciu Institute of Numerical Analysis)

Keywords

nonlinear equations in R; iterative methods; Halley-Aitken method.

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I. Păvăloiu, A Halley-Aitken-type method for approximating the solutions of scalar equations, Bul. Ştiinţ. Univ. Baia Mare, 17 (2001) nos. 1-2, pp. 85-92.

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A Halley-Aitken type method for approximating the solutions of scalar equations

Ion Păvăloiu

1 Introduction

Let f:[a,b]→ℝ, where a,b∈ℝ, a<b, and suppose that f has the first order derivative, which is positive: f′⁢(x)>0,∀x∈[a,b]. Consider the function h:[a,b]→ℝ

(1.1) h⁢(x)=f⁢(x)f′⁢(x).

In [2] there is shown that the Halley method for solving

(1.2) f⁢(x)=0

is in fact the Newton method for solving (1.1). This method consists therefore in generating the sequence (xn)n≥0 by

(1.3) xn+1=xn−h⁢(xn)h′⁢(xn),x0∈[a,b],n=0,1,…,.

The first and second order derivatives of h are given by

(1.4) h′⁢(x)=2⁢[f′⁢(x)]2−f′′⁢(x)⁢f⁢(x)2⁢[f′⁢(x)]3/2,x∈[a,b]

and

(1.5) h′′⁢(x)=[3⁢[f′′⁢(x)]2−2⁢f′′′⁢(x)⁢f′⁢(x)]⁢f⁢(x)4⁢[f′⁢(x)]5/2,x∈[a,b].

These relations imply

(1.6) h′⁢(x¯)=[f′⁢(x¯)]1/2

and

(1.7) h′′⁢(x¯)=0

where x¯∈[a,b] denotes the solution of (1.2). As shown in [1], equality (1.7) characterizes the Halley method, in the sense that ensures its convergence order 3. The authors of [4], analyzing an algorithm of Heron for approximating 1003, give a general algorithm which can be used for approximating the cubic root of any real positive number.

In [7] it is shown that the algorithm from [4] is nothing else than the chord method applied to equation h⁢(x)=0 where h⁢(x)=f⁢(x)f′⁢(x), with f⁢(x)=x3−N. In this case the equation h⁢(x)=0 has the form x2−Nx=0, when N>0, N∈ℝ.

It is clear that between the Heron algorithm and the Halley method there exists a connection, in the sense that the transformed equation to which we apply the Newton or the chord method is the same. In [7] and [10], the authors study the convergence and error bounds for the Steffensen and Aitken-Steffensen methods applied to (1.1). In this note we shall study a variant of the Aitken-Steffensen method, which differs from those presented in [10] and [11].

We shall consider other two equations, equivalent to (1.2), having the form

(1.8) x−φ1⁢(x)=0

and

(1.9) x−φ2⁢(x)=0,

where φ1,φ2:[a,b]→[a,b] will be convenably chosen.

We shall study the sequence (xn)n≥0 given by

(1.10) xn+1=φ1⁢(xn)−h⁢(φ1⁢(xn))[φ1⁢(xn),φ2⁢(φ1⁢(xn));h],x0∈[a,b],n=0,1,….

We shall consider the following assumptions on f,φ1 and φ2:

i. f∈C4⁢[a,b];

ii. equation (1.2) has a solution x¯∈(a,b);

iii. f′⁢(x)>0, ∀x∈[a,b];

iv. φ1 obeys 0<[x,y;φ1]<1,∀x,y∈[a,b], where [x,y;φ1] denotes the first order divided difference of φ1 on x and y:

[x,y;φ1]=(φ1⁢(y)−φ1⁢(x))/(y−x);

v. φ2 obeys −1<[x,y;φ2]<0,∀x,y∈[a,b].

2 The local convergence and error bounds

We shall use the following identities:

(2.1) φ1⁢(xn)−h⁢(φ1⁢(xn))[φ1⁢(xn),φ2⁢(φ1⁢(xn));h] =φ2⁢(φ1⁢(xn))−h⁢(φ2⁢(φ1⁢(xn)))[φ1⁢(xn),φ2⁢(φ1⁢(xn));h]
n =0,1,…,.

and also the Newton identity

(2.2) h⁢(x)=h⁢(y)+[y,z;h]⁢(x−y)+[x,y,z;h]⁢(x−y)⁢(x−z)

where [x,y,z;h] is the second order divided difference of h on x,y,z.

We notice that equality (1.6) and hypothesis i. ensure the existence of α,β∈ℝ, a≤α<x¯<β≤b such that h′⁢(x)>0 ∀x∈[α,β].

The following theorem holds:

Theorem 2.1

Let [α,β]⊆[a,b] be such that h′⁢(x)>0 ∀x∈[α,β]. If the functions f,φ1,φ2 and the initial approximation x0 satisfy:
a) x0∈[α,β] can be chosen such that φ1⁢(x0)∈[α,β] and φ2⁢(φ1⁢(x0))∈[α,β];
b) the hypotheses i-v an satisfied.
Then the following properties are true:

j. for all n∈ℕ we have

|xn+1−x¯|≤max⁡{|xn+1−φ1⁢(xn)|,|xn+1−φ2⁢(φ1⁢(xn))|};

jj. there exists k>0, k∈ℝ, which does not depend on n, such that

|xn+1−x¯|≤k⁢|xn−x¯|3,∀n∈ℕ;

jjj. if x0 is close enough to x¯ to obey k⁢|x¯−x0|<1, then the sequences (xn)n≥0, (φ1⁢(xn))n≥0 and (φ2⁢(φ1⁢(xn)))n≥0 converge to their common limit x¯.

Proof. We shall analyses two cases.

I. x0<x¯. Then φ1⁢(x0)−x¯=φ1⁢(x0)−φ1⁢(x¯)=[x0,x¯;φ1]⁢(x0−x¯)<0, i.e., φ1⁢(x0)<x¯. Denote Ψ⁢(x)=x−φ1⁢(x), and so Ψ⁢(x0)−Ψ⁢(x¯)=[x0,x¯;Ψ]⁢(x0−x¯)=[1−[x0,x¯,φ1]]⁢(x0−x¯)<0, i.e. x0<φ1⁢(x0). Now we show that φ2⁢(φ1⁢(x0))>x¯. From φ1⁢(x0)<x¯ it follows φ2⁢(φ1⁢(x0))−x¯=φ2⁢(φ1⁢(x0))−φ2⁢(x¯)=[x¯,φ1⁢(x0);φ2]⁢(φ1⁢(x0)−x¯)>0, i.e. φ2⁢(φ1⁢(x0))>x¯. Next, we show that x1∈[φ1⁢(x0),φ2⁢(φ1⁢(x0))], where x1 is obtained from (1.10) for n=0. Since h′⁢(x)>0,∀x∈[α,β], and φ1⁢(x0)∈[α,β], we get that h⁢(φ1⁢(x0))<0 (we know that φ1⁢(x0)<x¯) and so x1satisfies x1>φ1⁢(x0). We have used the fact that h′⁢(x)>0⁢∀x∈[α,β] implies [φ1⁢(x0),φ2⁢(φ1⁢(x0));h]>0. Now we show that x1<φ2⁢(φ1⁢(x0)). This inequality follows from φ2⁢(φ1⁢(x0))>x¯, h⁢(φ2⁢(φ1⁢(x0)))>0 and from (2.1) for n=0. we have shown that

(2.3) x0<φ1⁢(x0)<x¯<φ2⁢(φ1⁢(x0))

and

(2.4) x1∈(φ1⁢(x0),φ2⁢(φ1⁢(x0))).

II. x0>x¯. Similarly to the above reason, we get that

(2.5) x0>φ1⁢(x0)>x¯>φ2⁢(φ1⁢(x0))

and

(2.6) x1∈(φ2⁢(φ1⁢(x0)),φ1⁢(x0)).

Denoting by I0 the open interval determined by φ1⁢(x0) and φ2⁢(φ1⁢(x0)), then obviously relations (2.3) - (2.6) may be sinthetized as

x1,x¯∈I0.

It can be easily seen that if we denote by I1 the open interval determined by φ1⁢(x1) and φ2⁢(φ1⁢(x1)) then get

I1⊂I0

and

x2,x¯∈I1

where x2 is obtained from (1.10) for n=1.

Let In be the open interval determined by φ1⁢(xn) and φ2⁢(φ1⁢(xn)) for some n∈ℕ. Then repeating the above reason, we may show that

(2.7) x¯,xn+1∈In

and

In+1⊂In,

where In+1 is determined by φ1⁢(xn+1) and φ2⁢(φ1⁢(xn+1)). From the above reason and from (2.7) it follows j., which yields an error bound bound for each iteration step.

For jj. using identity (2.2) we get

h⁢(x¯) =h⁢(φ1⁢(xn))+[φ1⁢(xn),φ2⁢(φ1⁢(xn));h]⁢(x¯−φ1⁢(xn))+
[φ1⁢(xn),φ2⁢(φ1⁢(xn)),x¯;h]⁢(x¯−φ1⁢(xn))⁢(x¯−φ2⁢(φ1⁢(xn)))

whence, taking into account (1.10) and h⁢(x¯)=0, we get

(2.8) x¯−xn+1=[φ1⁢(xn),φ2⁢(φ1⁢(xn)),x¯;h][φ1⁢(xn),φ2⁢(φ1⁢(xn));h]⁢(x¯−φ1⁢(xn))⁢(x¯−φ2⁢(φ1⁢(xn))).

The mean value formulae for the divided differences lead us to

(2.9) [φ1⁢(xn),φ2⁢(xn);h]=h′⁢(θn),θn∈In

and

[φ1⁢(xn),φ2⁢(φ1⁢(xn)),x¯;h]=h′′⁢(ηn)2,ηn∈In.

From i. and using the Lagrange formula it follows

(2.10) h′′⁢(ηn)=h′′⁢(ηn)−h′′⁢(x¯)=h′′′⁢(ξn)⁢(ηn−x¯),ηn∈In.

Denoting

m1=infx∈[α,β]|h′⁢(x)|

and

M1=supx∈[α,β]|h′′′⁢(x)|,

from (2.8) and taking into account (2.9) and (2.10) we get

|x¯−xn+1|≤M12⁢m1⁢|x¯−φ1⁢(xn)|⁢|x¯−φ2⁢(φ1⁢(xn))|⁢|x¯−ηn|.

The property jj. follows easily by denoting k=M12⁢m1 and taking into account iv, v, and the fact that ηn∈In.

Property jjj is an immediate consequence of j and jj.  

3 Determining the functions φ1 and φ2

we shall present a modality of choosing φ1 and φ2 in order to obey the assumptions of Theorem 2.1

Suppose that f is strictly convex on [a,b], i.e. f′′⁢(x)>0,∀x∈[a,b]. This assumption, together with f′⁢(x)>0 ∀x∈[a,b], lead, by (1.4) to h′⁢(x)>0⁢∀x∈[a,x¯]. Relation (1.4) again and f′⁢(x)>0 and f⁢(x¯)=0 imply the existence of β, x¯<β≤b such that h′⁢(x)>0,∀x∈[x¯,β].These hypotheses ensure the existence of an interval [α,β] for which h′⁢(x)>0,∀x∈[α,β]. Since f′′⁢(x)>0 it follows that f′⁢(x) is increasing on [a,b].

Taking

φ1⁢(x)=x−1μ⁢f⁢(x)

and

φ2⁢(x)=x−1λ⁢f⁢(x),

with μ≥fs′⁢(b) and 0<λ≤fd′⁢(a), and assuming that 0<f′⁢(x)<2⁢λ,∀x∈[a,b], then the functions φ1 and φ2 defined above obey hypotheses iv and v of Theorem 2.1. For a≤x0≤x¯ in Theorem 2.1, hypothesis φ1⁢(x0)∈[α,β] is automatically verified, but the assumption φ2⁢(φ1⁢(x0))∈[α,β] must be kept.

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