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analysis.convex.specific_functions.deriv

Collection of convex functions #

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In this file we prove that certain specific functions are strictly convex, including the following:

TODO #

These convexity lemmas are proved by checking the sign of the second derivative. If desired, most of these could also be switched to elementary proofs, like in analysis.convex.specific_functions.basic.

theorem strict_convex_on_pow {n : ℕ} (hn : 2 ≤ n) :
strict_convex_on ℝ (set.Ici 0) (λ (x : ℝ), x ^ n)

x^n, n : ℕ is strictly convex on [0, +∞) for all n greater than 2.

theorem even.strict_convex_on_pow {n : ℕ} (hn : even n) (h : n ≠ 0) :

x^n, n : ℕ is strictly convex on the whole real line whenever n ≠ 0 is even.

theorem finset.prod_nonneg_of_card_nonpos_even {α : Type u_1} {β : Type u_2} [linear_ordered_comm_ring β] {f : α → β} [decidable_pred (λ (x : α), f x ≤ 0)] {s : finset α} (h0 : even (finset.filter (λ (x : α), f x ≤ 0) s).card) :
0 ≤ s.prod (λ (x : α), f x)
theorem int_prod_range_nonneg (m : ℤ) (n : ℕ) (hn : even n) :
0 ≤ (finset.range n).prod (λ (k : ℕ), m - ↑k)
theorem int_prod_range_pos {m : ℤ} {n : ℕ} (hn : even n) (hm : m ∉ set.Ico 0 ↑n) :
0 < (finset.range n).prod (λ (k : ℕ), m - ↑k)
theorem strict_convex_on_zpow {m : ℤ} (hm₀ : m ≠ 0) (hm₁ : m ≠ 1) :
strict_convex_on ℝ (set.Ioi 0) (λ (x : ℝ), x ^ m)

x^m, m : ℤ is convex on (0, +∞) for all m except 0 and 1.

theorem has_deriv_at_sqrt_mul_log {x : ℝ} (hx : x ≠ 0) :
has_deriv_at (λ (x : ℝ), √ x * real.log x) ((2 + real.log x) / (2 * √ x)) x
theorem deriv_sqrt_mul_log (x : ℝ) :
deriv (λ (x : ℝ), √ x * real.log x) x = (2 + real.log x) / (2 * √ x)
theorem deriv_sqrt_mul_log'  :
deriv (λ (x : ℝ), √ x * real.log x) = λ (x : ℝ), (2 + real.log x) / (2 * √ x)
theorem deriv2_sqrt_mul_log (x : ℝ) :
deriv^[2] (λ (x : ℝ), √ x * real.log x) x = -real.log x / (4 * √ x ^ 3)