4 papers
Penalized likelihood estimation of probability density functions using compositional splines
Stanislav Škorňa, Jitka Machalová
Probability density functions are commonly estimated through preliminary smoothing or aggregation procedures, e.g., histograms or kernel density estimation, before subsequent funct…
Compositional Periodic Spline Approximation for Circular Density Data in Bayes Spaces
Jitka Machalová, Jana Heckenbergerová, Karel Hron
This paper proposes a novel framework for the approximation and analysis of circular density data using compositional periodic splines within Bayes spaces with the Hilbert space st…
Approximation of bivariate densities with compositional splines
Stanislav Å korÅa, Jitka Machalová, Jana Burkotová +2
Reliable estimation and approximation of probability density functions is fundamental for their further processing. However, their specific properties, i.e. scale invariance and re…
Efficient spline orthogonal basis for representation of density functions
Jana Burkotová, Ivana Pavlů, Hiba Nassar +2
Probability density functions form a specific class of functional data objects with intrinsic properties of scale invariance and relative scale characterized by the unit integral c…