140 CHAPTER 5. FUNCTIONS ON NORMED LINEAR SPACES

If f ≥ 0, then the mean value theorem implies that for some

t ∈ (a,b) ,F (b)−F (a) =∫ b

af dx = f (t)(b−a)≥ 0.

Thus ∫ b

a(| f |− f )dx≥ 0,

∫ b

a(| f |+ f )dx≥ 0

and so∫ b

a | f |dx≥∫ b

a f dx and∫ b

a | f |dx≥−∫ b

a f dx so this proves∣∣∣∫ b

a f dx∣∣∣≤ ∫ b

a | f |dx. This,

along with part 2 implies the other claim that∣∣∣∫ b

a f dx∣∣∣≤ ∣∣∣∫ b

a | f |dx∣∣∣.

The last claim is obvious because an antiderivative of 1 is F (x) = x. ■Note also that the usual change of variables theorem is available because if F ′ = f , then

f (g(x))g′ (x) = ddx F (g(x)) so that, from the above proposition,

F (g(b))−F (g(a)) =∫ g(b)

g(a)f (y)dy =

∫ b

af (g(x))g′ (x)dx.

We usually let y = g(x) and dy = g′ (x)dx and then change the limits as indicated above,equivalently we massage the expression to look like the above. Integration by parts alsofollows from differentiation rules.

Consider the iterated integral∫ b1

a1· · ·∫ bp

apαxα1

1 · · ·xα pp dxp · · ·dx1. It means just what it

meant in calculus. You do the integral with respect to xp first, keeping the other variablesconstant, obtaining a polynomial function of the other variables. Then you do this one withrespect to xp−1 and so forth. Thus, doing the computation, it reduces to

α

p

∏k=1

(∫ bk

ak

xαkk dxk

)= α

p

∏k=1

(bαk+1

αk +1− aαk+1

αk +1

)and the same thing would be obtained for any other order of the iterated integrals. Sinceeach of these integrals is linear, it follows that if (i1, · · · , ip) is any permutation of (1, · · · , p) ,then for any polynomial q,∫ b1

a1

· · ·∫ bp

ap

q(x1, ...,xp)dxp · · ·dx1 =∫ bi1

aip

· · ·∫ bip

aip

q(x1, ...,xp)dxip · · ·dxi1

Now let f : ∏pk=1 [ak,bk]→ R be continuous. Then each iterated integral results in a con-

tinuous function of the remaining variables and so the iterated integral makes sense. Forexample, by Proposition 5.9.5,

∣∣∣∫ dc f (x,y)dy−

∫ dc f (x̂,y)dy

∣∣∣=∣∣∣∣∫ d

c( f (x,y)− f (x̂,y))dy

∣∣∣∣≤ maxy∈[c,d]

| f (x,y)− f (x̂,y)|< ε

if |x− x̂| is sufficiently small, thanks to uniform continuity of f on the compact set [a,b]×[c,d]. Thus it makes perfect sense to consider the iterated integral

∫ ba∫ d

c f (x,y)dydx. Thenusing Proposition 5.9.5 on the iterated integrals along with Theorem 5.7.1, there exists asequence of polynomials which converges to f uniformly {pn} . Then applying Proposition5.9.5 repeatedly,∣∣∣∣∣

∫ bi1

aip

· · ·∫ bip

aip

f (x)dxp · · ·dx1−∫ bi1

aip

· · ·∫ bip

aip

pn (x)dxp · · ·dx1

∣∣∣∣∣

140 CHAPTER 5. FUNCTIONS ON NORMED LINEAR SPACESIf f > 0, then the mean value theorem implies that for somete (a.b).F (0) F(a) = [ fax= f(Q(b-a) >0.Thus ‘ ,[ii-narzo, [fit narzoand so 2 |fldx> J? fdx and f? |fldx > — ff? fdx so this provesI? fax < [? |f\dx. This,Je flaxThe last claim is obvious because an antiderivative of 1 is F (x) =x. llNote also that the usual change of variables theorem is available because if F’ = f, thenf (g(x)) 2! (x) = 4F (g(x)) so that, from the above proposition,xalong with part 2 implies the other claim that | f iM fas| <g(b)Ped) ~P(e(a))= [" Fo)ay= [Flee )dWe usually let y = g(x) and dy = 9’ (x) dx and then change the limits as indicated above,equivalently we massage the expression to look like the above. Integration by parts alsofollows from differentiation rules.Consider the iterated integral I oe Ie? ax(! «x5? dxp++-dxy. It means just what itmeant in calculus. You do the integral with respect to x, first, keeping the other variablesconstant, obtaining a polynomial function of the other variables. Then you do this one withrespect to X»_; and so forth. Thus, doing the computation, it reduces toP by a Pp pot qQhkta xikdx, ) =a ost(/, k : Ges —)and the same thing would be obtained for any other order of the iterated integrals. Sinceeach of these integrals is linear, it follows that if (i;,--- ,ip) is any permutation of (1,--- ,p),then for any polynomial gq,by bp bi, Dip/ ve G (X15 0+,Xp) AXp +++ dxy =| | (X15 +5 Xp) dx; dX,aj a ip ipPpNow let f: Me, [ax, bg] + R be continuous. Then each iterated integral results in a con-tinuous function of the remaining variables and so the iterated integral makes sense. ForIe f(xsy)dy~ [EF (&y)dy| _example, by Proposition 5.9.5,d[/1l9) F669) 4] < max IF.) —Fy)1 <eif |x — | is sufficiently small, thanks to uniform continuity of f on the compact set [a,b] x[c,d]. Thus it makes perfect sense to consider the iterated integral fe f “a f (x,y) dydx. Thenusing Proposition 5.9.5 on the iterated integrals along with Theorem 5.7.1, there exists asequence of polynomials which converges to f uniformly {p,}. Then applying Proposition5.9.5 repeatedly,bi, Dip biy Dip| eae f(a) dxp--dxi— [ eae Pn (&) dXp-+-dx)Yip qjdip ip Tip