The Convergences Comparison between the Halley’s Method and Its Extended One Based on Formulas Derivation and Numerical Calculations ()
1. Introduction
In 1673, Yoshimasu Murase [1] made a cubic equation to obtain the thickness of a hearth. He introduced two kinds of recurrence formulas of square
and the deformation. We find that the three formulas lead to a Horner’s method (Horiguchi, [2] ) and an extension of Newton’s method (Horiguchi, [3] ). This shows originality of Wasan (mathematics developed in Japan) in the Edo era (1603-1868). We do research similar to Horiguchi, [3] against the Halley’s method. We give function
defined from
for extension of Halley’s method.
From now on, let
be a real number, and a function
times differentiable if necessary, and
continuous.
Definition 1.1. Let
where
is a real number that is not 0. We define the function g(t) such as
(1)
Because
, the graph of
extends or contracts by
in the
-axis, without changing the height of
. Expansion and contraction come to object in
and
.
Theorem 1.2. The formulas

give the convex upward (the convex downward resp.) at the point
of graph of
.
Proof. It is proved by the next calculations.
(4)
(5)
□
From the formulas (4), (5), we obtain the next theorem.
Theorem 1.3. The curvature of the cure
at the point
is formulas (6) and (7).
![]()
These become the curvature
of
if
in particular.
Proof. Formula (6) is obtained by substituting the formulas (4) and (5) for
in the curvature
. □
Theorem 1.4. A necessary and sufficient condition for
(8)
is that formula (9) holds.
(9)
Proof. Formula (9) is obtained from (8). □
Proposition 1.5. If
is a simple root (
multiple root resp.) of
, then
becomes the simple root (
multiple root resp.) of
.
2. Halley’s Method and Extension of Halley’s Method
Definition 2.1. The recurrence formula to approximate a root of the equation ![]()
(10)
is called Halley’s method1.
Halley’s method is obtained by improving the Newton’s method (11) (Ref. [5] ).
(11)
They are methods of giving the initial value
, calculating
one after another, and to determine for a root.
From now on we omit the notation
in recurrence formulas. Applying the Halley’s method to
, we get
(12)
If we express this by formula (1) in
, then we get the next definition.
Definition 2.2. Let α be a root of the equation
. (13) is the recurrence formula to approximate
. We call this the
-th power of the extension of Halley’s method (EH-method).
(13)
Here, if
then the formula (13) becomes Halley’s method.
Calculation formula of
-th power of EH-method is this.
(14)
3. Formulas to Compare the Convergences for Extensions of Halley’s Method
Theorem 3.1. Let
be a simple root for
, i.e.,
. Then Halley’s method becomes the following third-order convergence.
(15)
If
is
(
) multiple root, then it becomes the following linearly convergence.
(16)
Proof. There is a brief proof of (15) in wikipedia [4] . Therefore we go to the proof of (16).
We merely sketch
with
. Since
is represented as
(17)
is as follows, respectively.
(18)
From these formulas, we obtain the following linearly convergence.
(19)
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Lemma 3.2. In the sequence
, let
, and
,
an arbitrary real constant number that is not 0, respectively. In this case following formula holds for large enough integer
.
(20)
Proof. Applying L’Hospital’s rule to
, formula (20) is obtained.
□
Theorem 3.3. Let the condition be the same as Theorem 3.1. If
sufficiently close to
,then
-th power of EH-method (Extended Halley’s method) becomes the third-order convergence of the following formula.
(21)
If
is
(
) multiple root, then it will be linearly convergence of the following formula.
(22)
Proof. If
is a simple root for
, then
also becomes a simple root for
. In this case Halley’s method for
becomes the third-order convergence of the following formula.
(23)
Here
become the followings.
(24)
Therefore we obtain
(25)
By lemma 3.2, we get
(26)
Therefore, formula (25) becomes
(27)
By changing the independent variable
of the functions
and
in numerator to
, we obtain (21).
In case that
is
multiple root, by (16), (1) and (20) we obtain
(28)
□
Theorem 3.4. Let
be a simple root of
. Then a necessary and sufficient condition for the convergence to
of
-th power of EH-method is equal to or faster than Halley’s method is that
satisfies the following conditions.
(29)
That is
(30)
Proof. Compare the coefficient of
of the third-order convergence of
-th power of EH-method and that in the case of Halley’s method. Then the necessary and sufficient condition is equivalent to the next formula.
(31)
The formula (29) is obtained from this. □
Corollary 3.5. (1) If
then (30) becomes
(32)
(2) If
then (30) becomes
(33)
We transform the equation
into
. That is, two equations have the same root.
-th power of EH-method for
is
(34)
and if
is a simple root, then it becomes the third-order convergence (35).
(35)
We get the following by comparing the coefficient of
of formula (21) and (35).
Proposition 3.6. Let
, and
a simple root. Then a necessary and sufficient condition for the convergence to
of
-th power of EH-method (Extended Halley’s method) (13) of
to be equal to or faster than that
-th power of EH-method (34) of
is that the real numbers
and
satisfy the following condition (36).
(36)
Theorem 3.7. Let
be a simple root for
, i.e.,
. Inequality (29) is represented by the second derivative
(37)
which distinguishes the convex-concave of the curve
. It shows the next complicated inequalities (38), (39).
(i) ![]()
(38)
(ii) ![]()
(39)
Proof. We lead inequalities (38), (39) from (29). Let
(40)
Then inequality (29) becomes
(41)
(42)
We transform the formula B.
(43)
Therefore inequality (29) becomes (44).
(44)
Furthermore, we transform the inequality.
(45)
From (45), we get (38), (39) according to plus, minus number of
respectively. □
Theorem 3.8. Let the condition be the same as the above Theorem. Inequality (29) is represented by the curvature
(46)
Those are the next complicated inequalities (47) and (48).
(i) ![]()
(47)
(ii) ![]()
(48)
Proof. We get (47), (48) by dividing formula (38), (39) in
, respectively.
4. Convergence Comparisons by the Numerical Calculations of Halley’s Method and Extensions of Halley’s Method
We perform numerical calculations by the calculation formula (14) in the standard format in Excel 2013 of Microsoft. We perform numerical calculations for various equations such as
-th order equations (
), equations of trigonometric, exponential, logarithmic function, respectively.
In the examples of the followings, there are cases where some numerical calculations do not fit in with the inequality (30) a little. Those are probably due to the formula (21) the approximate formula, choosing the initial value
, and the accuracy of using the standard format in Excel is insufficient. However, the results to fit the theories generally have been obtained.
Example 4.1. A quadratic equation
(49)
The roots of (49) are
. Because
, in case of
, condition (33) becomes
(50)
We choose real numbers
and initial values
such as Table 1, Table 2, and do numerical computations. We explain how to read Table 1. The first column represents the initial value
and the absolute error, and the first row represents the real number
of
.
Two numbers 1 and 1.11022E−16 of intersection of two row and two column mean the following.
Number 1 indicates the number of iterations that Halley’s method
to converge to the root 1. 1.11022E−16 indicates the absolute error |the value
of the convergence of the numerical calculation―root 1|. If two iteration numbers are the same for the same initial value
, then we evaluate the convergences by the absolute errors. In the Table 1, Table 2, all
-th power of EH-method (Extension of Halley’s method) converge in root 1 at iteration number
. But, for the same initial value
, each column of EH-method
has the absolute errors (at least one) that are equal to or smaller than Halley’s method
in the ranges of (50).
We confirm Theorem 3.7. Because
in
, inequality (39) is applied. In this case (39) becomes the following inequality.
(51)
The results are Table 3. The range of
which satisfies (51) becomes
.
Example 4.2. A cubic equation
(52)
Because the root of (52) is 2, the condition (30) becomes
(53)
We choose real numbers
and initial values
such as Table 4, Table 5, and do numerical computations. All iteration numbers are 2 or 3. But, for the same initial value
![]()
Table 1. Calculations of (14) for root 1, −0.041 ≤ q ≤ 1.
![]()
Table 2. Calculations of (14) for root 1, 23 ≤ q ≤ 24.042.
![]()
Table 3. Calculations of (51) for root 1, −0.041 ≤ q ≤ 1.
![]()
Table 4. Calculations of (14) for root 2, −1.8875 ≤ q ≤ −1.462.
![]()
Table 5. Calculations of (14) for root 2, 1 ≤ q ≤ 1.4262.
, each column of EH-method
has the absolute errors (at least one) that are equal to or smaller than Halley’s method
in the ranges of (53).
Example 4.3. A cubic equation
(54)
In case of the root 1, the condition (30) becomes
(55)
We choose real numbers
and initial values
such as Table 6, Table 7, and do numerical computations. Each initial value
, iteration number of EH-method
and Halley’s method
are the same. But, for the same initial value
, each column of EH-method
has the absolute errors (at least one) that are smaller than Halley’s method
in the ranges of (55).
Example 4.4.
(56)
The roots of (56) are
The condition (30) becomes
(57)
If we take the root in
, then (57) becomes
(58)
We do numerical computations for the real numbers
and initial values
in Table 8, Table 9. All iteration numbers in Table 8 are 1. But, for the same initial value
, each column of EH-method
has the absolute errors (at least one) that are smaller than Halley’s method
in
. In case of
, number of iterations of EH-methods
are small than Halley’s method.
![]()
Table 6. Calculations of (14) for root 1, −0.1934 ≤ q ≤ 1.
![]()
Table 7. Calculations of (14) for root 1, 35 ≤ q ≤ 36.
![]()
Table 8. Calculations of (14) for root π, −0.3455 ≤ q ≤ 0.458.
Example 4.5.
(59)
The roots of (59) are
The condition (30) becomes
(60)
If we take the root in
, then (60) becomes
(61)
Table 10 gives numerical computations. In case of
, EH-methods
have better approximate degrees than Halley’s method
in
.
Example 4.6.
(62)
The root of (62) is 1. The condition (30) becomes
(63)
Table 11 and Table 12 give the numerical values to almost adapt to Theorem 3.4.
Example 4.7.
(64)
The root of (64) is 1. The condition (30) becomes
(65)
Table 13 and Table 14 give the numerical values to almost adapt to Theorem 3.4.
![]()
Table 9. Calculations of (14) for root π, 1 ≤ q ≤ 1.8043.
![]()
Table 10. Calculations of (14) for root π, 0.46 ≤ q ≤ 1.
![]()
Table 11. Calculations of (14) for root 1, −13.14142 ≤ q ≤ −13.
![]()
Table 12. Calculations of (14) for root 1, 1 ≤ q ≤ 1.14142.
![]()
Table 13. Calculations of (14) for root 1, 1 ≤ q ≤ 1.2041684.
![]()
Table 14. Calculations of (14) for root 1, 10.795834 ≤ q ≤ 11.
Acknowledgements
Dr. Hideko Nagasaka (Nihon University former professor) taught me numerical computations. I am deeply grateful to her.
NOTES
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1Edmond Halley (1656-1742) is the British astronomer, and famous for Halley’s comet of research.