With Density #
For an s-finite kernel κ : kernel α β and a function f : α → β → ℝ≥0∞ which is finite
everywhere, we define withDensity κ f as the kernel a ↦ (κ a).withDensity (f a). This is
an s-finite kernel.
Main definitions #
ProbabilityTheory.kernel.withDensity κ (f : α → β → ℝ≥0∞): kernela ↦ (κ a).withDensity (f a). It is defined ifκis s-finite. Iffis finite everywhere, then this is also an s-finite kernel. The class of s-finite kernels is the smallest class of kernels that contains finite kernels and which is stable bywithDensity. Integral:∫⁻ b, g b ∂(withDensity κ f a) = ∫⁻ b, f a b * g b ∂(κ a)
Main statements #
ProbabilityTheory.kernel.lintegral_withDensity:∫⁻ b, g b ∂(withDensity κ f a) = ∫⁻ b, f a b * g b ∂(κ a)
Kernel with image (κ a).withDensity (f a) if Function.uncurry f is measurable, and
with image 0 otherwise. If Function.uncurry f is measurable, it satisfies
∫⁻ b, g b ∂(withDensity κ f hf a) = ∫⁻ b, f a b * g b ∂(κ a).
Equations
- One or more equations did not get rendered due to their size.
Instances For
If a kernel κ is finite and a function f : α → β → ℝ≥0∞ is bounded, then withDensity κ f
is finite.
Auxiliary lemma for IsSFiniteKernel.withDensity.
If a kernel κ is finite, then withDensity κ f is s-finite.
For an s-finite kernel κ and a function f : α → β → ℝ≥0∞ which is everywhere finite,
withDensity κ f is s-finite.
For an s-finite kernel κ and a function f : α → β → ℝ≥0, withDensity κ f is s-finite.
Equations
- One or more equations did not get rendered due to their size.