For nonzero vectors x and y in the normed linear space (X, ‖ ⋅ ‖), we can define the p-angular distance by α p x y : = x p − 1 x − y p − 1 y . $$ {\alpha}_p\left[x,y\right]:=\left\Vert {\left\Vert x\right\Vert}^{p-1}x-{\left\Vert y\right\Vert}^{p-1}y\right\Vert . $$
We show (among other results) that, for p ≥ 2, α p x y ≤ p y − x ∫ 0 1 1 − t x + t y p − 1 d t ≤ p y − x x p − 1 + y p − 1 2 + x + y 2 p − 1 ≤ p y − x x p − 1 + y p − 1 2 ≤ p y − x max x y p − 1 , $$ \begin{array}{l}{\alpha}_p\left[x,y\right]\le p\left\Vert y-x\right\Vert {\displaystyle \underset{0}{\overset{1}{\int }}{\left\Vert \left(1-t\right)x+ty\right\Vert}^{p-1}dt}\hfill \\ {}\kern3.36em \le p\left\Vert y-x\right\Vert \left[\frac{{\left\Vert x\right\Vert}^{p-1}+{\left\Vert y\right\Vert}^{p-1}}{2}+{\left\Vert \frac{x+y}{2}\right\Vert}^{p-1}\right]\hfill \\ {}\kern3.36em \le p\left\Vert y-x\right\Vert \frac{{\left\Vert x\right\Vert}^{p-1}+{\left\Vert y\right\Vert}^{p-1}}{2}\le p\left\Vert y-x\right\Vert {\left[ \max \left\{\left\Vert x\right\Vert, \left\Vert y\right\Vert \right\}\right]}^{p-1},\hfill \end{array} $$
for any x, y ∈ X. This improves a result of Maligranda from [“Simple norm inequalities,” Amer. Math. Month., 113, 256–260 (2006)] who proved the inequality between the first and last terms in the estimation presented above. The applications to functions f defined by power series in estimating a more general “distance” ‖f(‖x‖)x − f(‖y‖)y‖ for some x, y ∈ X are also presented.