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Guía 12: Optimización II. Concavidad y convexidad. Exámenes: Capítulos 9.5, 6.1. - Prof. 3, Apuntes de Negocios Internacionales

Una guía sobre el tema de la concavidad y la convexidad de las funciones diferenciables en segunda variable. El texto explica la relación entre la segunda derivada y la primera derivada, la definición de concavidad y convexidad, el cambio de concavidad y los puntos de inflexión. Además, se presentan ejemplos para estudiar la función y su representación gráfica.

Tipo: Apuntes

2016/2017

Subido el 12/01/2017

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Guide 12
Guide 12. Block 3: Optimization II.
Concavity and convexity.
S&H Chapters 9.5, 6.1
Recommended problems:
9.5: 1–9.
6.1: 5.
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pf5
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Guide 12. Block 3: Optimization II.

Concavity and convexity.

S&H Chapters 9.5, 6.

Recommended problems: 9.5: 1–9. 6.1: 5.

Index

Optimization II (a) The second derivative of a function (b) Concavity and convexity (c) Inflection points

Graphic representation of functions

Optimization II (b) Concavity and convexity

Definition of concavity and convexity for functions twice

differentiable

Given a function that is continuous in the interval [a, b] and twice differentiable in the interval (a, b), we say that (S&H p. 305):

  1. f (x) is convex in (a, b) ⇔ f ′′(x) ≥ 0 for all x ∈ (a, b) ⇔ f (x) has the shape “
  1. f (x) is concave on (a, b) ⇔ f ′′(x) ≤ 0 for all x ∈ (a, b) ⇔ f (x) has the shape “

Attention: sometimes the words “concave” and “convex” are used with different meanings in some books. We should check the definition in every book.

Optimization II (b) Concavity and convexity

Growth and concavity

Combining the possible growth and concavity of a function, we have 4 possible models: f (x) convex (f ′′(x) ≥ 0) “

f (x) concave (f ′′(x) ≤ 0) “

f (x) increasing (f ′(x) ≥ 0) 0 0

f (x) decreasing (f ′(x) ≤ 0) 0 0

Optimization II (c) Inflection points

Caracterization of inflection points

Theorem 1 (S&H Theorem 9.3)

If f is a function with a continuous second derivative in (a, b) and c ∈ (a, b), then

  1. If c is an inflection point, then f ′′(c) = 0.
  2. If f ′′(c) = 0 and f ′′^ changes sign at c, then c is an inflection point of f.

Optimization II (c) Inflection points

The graph of the inflection points

Optimization II (c) Inflection points

Summarizing:

f (x) =

x^3 −

x^2 −

x + 1

x − 1 1 / 2 2 Sign f ′(x) + 0 − 0 + Sign f ′′(x) − 0 + f (x) ↗ max ↘ min ↗ shape

i.p.

Graphic representation of functions

Graphic representation of functions

Summary of the procedure:

  1. Domain. Points of discontinuity and vertical asymptotes.
  2. Intersection points with the x axis (f (x) = 0).
  3. Sign of f (x) (recommended).
  4. Intersection points with the y axis.
  5. Stationary points.
  6. Local maximum and minimum points.
  7. Concavity, convexity and inflection points.
  8. Horizontal asymptotes. Recall: I (^) x = a is a vertical asymptote if limx→a f (x) = ±∞. I (^) y = A is an horizontal asymptote of f (x) at +∞ if limx→+∞ f (x) = A. I (^) y = B is an horizontal asymptote of f (x) at −∞ if limx→−∞ f (x) = B.