Block mixed norm 2026-10-06
The block mixed norm sums the norm of each block, for . Its dual norm is , where for and for . Apply Holder inequality blockwise and choose a norming block to attain equality. Absolute values are essential for signed components.
Let and use Nodewise Lasso with and nonzero design columns. Form with entry equal to one and other entries , and put row of equal to . The nodewise-Lasso residual identity and the Karush-Kuhn-Tucker conditions show that the diagonal of equals one and its row- off-diagonal entries have magnitude at most . For the Debiased Lasso,
The displayed bound follows row by row from Holder inequality. If the noise is conditionally multivariate normal with covariance , and the nodewise fits and tuning parameters depend only on , the first term is conditionally normal with covariance .
If satisfy , then
It follows by induction from the two-factor Holder inequality.
Group Lasso 2026-09-28
The group Lasso partitions a coefficient vector into groups and replaces the coordinatewise penalty with a weighted sum of group norms,
It tends to retain or discard an entire group at once. Its dual norm is
so the corresponding Holder inequality is .
For , nonnegative consumption with state-price budget satisfies this bound under CRRA utility. Apply Holder inequality on probability-times-time measure to and , with conjugate exponents and . If the price integral is finite, equality forces full budget use and . Financing this process is a separate feasibility issue, so the equality pattern alone does not assert attainability in an incomplete market.
For a zero-starting continuous local martingale , the stochastic exponential satisfies
The Holder inequality and the supermartingale property of the first exponential bound its stopped th moment by . The subtraction in the coefficient is , not a square root of .
Lp inclusion on a finite measure space Created 2026-09-24 Updated 2026-10-03
On a finite measure space, for . For , Hölder's inequality gives
with the same formula interpreted as when .
If , and , then the displayed bound follows by applying the Holder inequality to . Interpret the endpoint cases using the essential supremum. In particular convergence in Lp space and boundedness in a larger-exponent Lp space imply convergence at intermediate exponents.
Minkowski inequality Created 2026-10-05 Updated 2026-10-06
For , the Lp norm satisfies the triangle inequality. For , apply the Holder inequality to , then divide by when it is nonzero. The cases and follow directly from the pointwise triangle inequality. In particular, a series whose term norms have a finite sum converges in the complete space.
For a cube of side length in , , and a continuously differentiable function , its average satisfies
Averaging the fundamental theorem of calculus along a line segment from to and changing variables gives . The Holder inequality applies because , and the kernel norm is . Approximation extends the estimate to the continuous representative of a Sobolev space function. On it yields a Hölder continuous function of exponent representing every class.
Morrey's inequality 2026-10-06
For , every Sobolev space element has a Hölder continuous function representative of exponent , with the displayed bound. It also satisfies . Averaging the fundamental theorem of calculus along a line segment over a ball gives
The Holder inequality bounds this by , because . To compare two ball averages, translate a ball along the segment between their centres and use the same fundamental theorem of calculus along a line segment. These bounds give the displayed estimate. Density of smooth functions in a Sobolev space supplies the representative for nonsmooth . For , the corresponding conclusion is Lipschitz continuity.