Logarithmic mean

Logarithmic mean

In mathematics, the logarithmic mean is a function of two numbers which is equal to their difference divided by the logarithm of their quotient. In symbols:

:egin{matrix}M_{mbox{lm(x,y)&=lim_{(xi,eta) o(x,y)} frac{eta - xi}{ln eta - ln xi}\&=egin{cases}x & mbox{if }x=y \frac{y - x}{ln y - ln x} & mbox{else}end{cases}end{matrix}

for the positive numbers x, y.This measure is useful in engineering problems involving heat and mass transfer.

Inequalities

The logarithmic mean of two numbers is smaller than the arithmetic mean but larger than the geometric mean (unless the numbers are the same of course, in which case all three means are equal to the numbers):

: forall x>0 forall y>0 x e yRightarrow sqrt{xcdot y} < frac{y - x}{ln y - ln x} < frac{x+y}{2}

Derivation of the mean

Mean value theorem of differential calculus

From the mean value theorem: exists xiin [x,y] f'(xi) = frac{f(x)-f(y)}{x-y} the logarithmic mean is obtained as the value of xiby substituting ln for f: frac{1}{xi} = frac{ln x - ln y}{x-y} and solving for xi.: xi = frac{x-y}{ln x - ln y}

Integration

The logarithmic mean can also be interpreted as the area under an exponential curve.:L(x,y) = int_0^1 x^{1-t}cdot y^t mathrm{d}t(Check egin{array}{rcl} int_0^1 x^{1-t}cdot y^t mathrm{d}t&=& int_0^1 left(frac{y}{x} ight)^tcdot x mathrm{d}t \&=& xcdot int_0^1 expleft(tcdotln frac{y}{x} ight) mathrm{d}t \&=& frac{x}{ln frac{y}{x cdot left [ expleft(tcdotln frac{y}{x} ight) ight] _{t=0}^{1} \&=& frac{x}{ln frac{y}{x cdot left(frac{y}{x}-1 ight)end{array})

The area interpretation allows to easily derive basic properties of the logarithmic mean.Since the exponential function is monotonicthe integral over an interval of length 1 is bounded by x and y.The Homogenity of the integral operator is transferred to the mean operator,that is L(ccdot x, ccdot y) = ccdot L(x,y).

Generalization

Mean value theorem of differential calculus

You can generalize the mean to n+1 variables by considering the mean value theorem for divided differences for the nth derivative of the logarithm.You obtain:L_{mathrm{MV(x_0,dots,x_n) = sqrt [-n] {(-1)^{(n+1)}cdot n cdot ln [x_0,dots,x_n] }where ln [x_0,dots,x_n] denotes a divided difference of the logarithm.

For n=2 this leads to:L_{mathrm{MV(x,y,z) = sqrt{frac{(x-y)cdot(y-z)cdot(z-x)}{2cdot((y-z)cdotln x + (z-x)cdotln y + (x-y)cdotln z).

Integral

The integral interpretation can also be generalized to more variables,but it leads to a different result.Given the simplex Swith S = {(alpha_0,dots,alpha_n) : alpha_0+dots+alpha_n=1 land alpha_0ge0 land dots land alpha_nge0} and an appropriate measure mathrm{d}alpha which assigns the simplex a volume of 1, we obtain:L_{mathrm{I(x_0,dots,x_n) = int_S x_0^{alpha_0}cdotdotscdot x_n^{alpha_n} mathrm{d}alphaThis can be simplified using divided differences of the exponential function to:L_{mathrm{I(x_0,dots,x_n) = n!cdotexp [ln x_0, dots, ln x_n] .

Example n=2:L_{mathrm{I(x,y,z) = -2cdotfrac{xcdot(ln y-ln z) + ycdot(ln z-ln x) + zcdot(ln x-ln y)}{(ln x-ln y)cdot(ln y-ln z)cdot(ln z-ln x)}.

See also

* A different mean which is related to logarithms is the geometric mean.
* The logarithmic mean is a special case of the Stolarsky mean.

References

* [http://www.everything2.com/index.pl?node_id=801020 Logarithmic mean@Everything2.com]
* [http://jipam-old.vu.edu.au/v4n4/088_03.html Oilfield Glossary: Term 'logarithmic mean']
*


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