students

Data collected during 2004 and 2005 from students in statistics classes 
at a large state university in the northeastern United States.

In self-reported or anonymised data the user often encounters
    heaped data, i.e. data which are rounded (to a possibly different degree
    of coarseness). While this is mostly a minor problem in parametric density
    estimation the bias can be very large for non-parametric methods such as kernel
    density estimation. This package implements a partly Bayesian algorithm treating
    the true unknown values as additional parameters and estimates the rounding
    parameters to give a corrected kernel density estimate. It supports various
    standard bandwidth selection methods. Varying rounding probabilities (depending
    on the true value) and asymmetric rounding is estimable as well. Additionally,
    bivariate non-parametric density estimation for rounded data is supported.

Marcus Gross

Kernelheaping

Kernel Density Estimation for Heaped and Rounded Data

students function

http://mathfaculty.fullerton.edu/mori/Math120/Data/readme

students: Student0405

Description

Arguments

source