Differential Calculus: Several Variables (9hrs) · Engineering Mathematics - I

Taylor's theorem with various forms of remainders

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Taylor's theorem with various forms of remainders

1. Taylor for f(x,y)f(x,y) About (a,b)(a,b)

If ff has continuous partials up to order n+1n+1 near (a,b)(a,b), then for h=x−a,k=y−bh = x-a, k = y-b:

f(a+h,b+k)=f(a,b)+[hfx+kfy](a,b)+1/2![h2fxx+2hkfxy+k2fyy](a,b)+...+1/n![h∂/∂x+k∂/∂y]nf(a,b)+Rn+1f(a+h,b+k) = f(a,b) + [h f_x + k f_y]_{(a,b)} + 1/2! [h² f_{xx} + 2hk f_{xy} + k² f_{yy}]_{(a,b)} + ... + 1/n! [h ∂/∂x + k ∂/∂y]^n f_{(a,b)} + R_{n+1}

where [h∂/∂x+k∂/∂y]r[h ∂/∂x + k ∂/∂y]^r expands binomially, e.g. r=2r=2 gives h2fxx+2hkfxy+k2fyyh² f_{xx}+2hk f_{xy}+k² f_{yy}. This is the two-variable analogue of f(a+h)=f(a)+hf′+h2/2!f′′+...f(a+h)=f(a)+h f'+h²/2! f''+....

For (a,b)=(0,0)(a,b)=(0,0), this becomes Maclaurin.

2. Remainder Rn+1R_{n+1} — Three Usual Forms

Let (a+θh,b+θk)(a+θh, b+θk) be some intermediate point 0<θ<10<θ<1.

  • Lagrange form:
Rn+1=1/(n+1)![h∂/∂x+k∂/∂y]n+1f(a+θh,b+θk)R_{n+1}= 1/(n+1)! [h ∂/∂x + k ∂/∂y]^{n+1} f_{(a+θh, b+θk)}

— useful for bounds (estimate max derivative on segment).

  • Cauchy form:
Rn+1=1/n!(1−θ)n[h∂/∂x+k∂/∂y]n+1f(a+θh,b+θk)R_{n+1}= 1/n! (1-θ)^n [h ∂/∂x + k ∂/∂y]^{n+1} f_{(a+θh, b+θk)}

— sometimes sharper.

  • Peano / o-notation:
Rn+1=o((h2+k2)n/2)R_{n+1}= o((h²+k²)^{n/2})

meaning remainder smaller than ρnρ^n where ρ=√(h2+k2)ρ=√(h²+k²) — shows approximation order.

For exams, Lagrange suffices; mention others for completeness.

3. Linear and Quadratic Approximation (most used)

  • First-order (tangent plane):
f(a+h,b+k)≈f(a,b)+fxh+fykf(a+h,b+k) ≈ f(a,b)+ f_x h + f_y k

with error O(h2+k2)O(h²+k²).

  • Second-order: add 1/2[h2fxx+2hkfxy+k2fyy]1/2[h² f_{xx}+2hk f_{xy}+k² f_{yy}] — needed for maxima theory and error O(ρ3)O(ρ³).

4. Worked Examples

(a) Expand f(x,y)= e^x cos y about (0,0) to second order:
    f(0,0)=1, f_x= e^x cos y →1, f_y= -e^x sin y →0,
    f_{xx}= e^x cos y→1, f_{xy}= -e^x sin y→0, f_{yy}= -e^x cos y→-1
    ⇒ f(h,k) ≈ 1 + h + (h² - k²)/2 + R3 ; i.e. e^x cos y ≈1 + x + (x² - y²)/2 ✓
    Check: product of series e^x=1+x+x²/2, cos y=1-y²/2 confirms.

(b) Expand f(x,y)= sin(x+y) about (0,0) to third order: use single variable t=x+y
    sin t = t - t³/6 +... ⇒ f ≈ (x+y) - (x+y)³/6 ✓

(c) Estimate error for √(1+x+y) about (0,0) linear: √(1+h+k)≈1+(h+k)/2 ; Lagrange remainder
    = -(h+k)²/[8(1+θ(h+k))^{3/2}] ≤ (h+k)²/8 bounds ✓

(d) f(x,y)= log(1+x+y) : expansion log(1+t)=t -t²/2 +t³/3 ; t=x+y ⇒ log≈(x+y)-(x+y)²/2 ✓

5. Convergence and Use

Taylor's infinite series (Rn→0R_n→0) converges where ff analytic (polynomials, ex+ye^{x+y}, sin,cossin, cos everywhere; log(1+x+y)log(1+x+y) for ∣x+y∣<1|x+y|<1). Remainder estimate tells you how many terms keep error < tolerance.

6. Exam Points

  • State Taylor for f(x,y)f(x,y) about (a,b)(a,b) with Lagrange remainder — 5 marks, very frequent.
  • Expand ex+y,sin(x+y),log(1+x+y),√(1+x+y)e^{x+y}, sin(x+y), log(1+x+y), √(1+x+y) to second/third order about (0,0)(0,0) — 5-7 marks, very frequent.
  • Estimate remainder / error bound — 3-5 marks.
  • Second-order Taylor for maxima derivation (next topics) — 5 marks, frequent.
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