Maximum likelihood estimation of the concentration parameter of von Mises–Fisher distributions involves inverting the ratio <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$R_\nu=I_{\nu +1} / I_\nu $$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mrow> <msub> <mi>R</mi> <mi mathvariant="italic">ν</mi> </msub> <mo>=</mo> <msub> <mi>I</mi> <mrow> <mi mathvariant="italic">ν</mi> <mo>+</mo> <mn>1</mn> </mrow> </msub> <mo stretchy="false">/</mo> <msub> <mi>I</mi> <mi mathvariant="italic">ν</mi> </msub> </mrow> </math> </EquationSource> </InlineEquation> of modified Bessel functions and computational methods are required to invert these functions using...</equationsource></equationsource></inlineequation>

We reveal the boundary bias problem of Birnbaum–Saunders, inverse Gaussian, and reciprocal inverse Gaussian kernel estimators (Jin and Kawczak, 2003; Scaillet, 2004) and re-formulate these estimators to solve the problem. We investigate asymptotic properties of a new class of asymmetric kernel...