Non‐parametric Estimation of the Residual Distribution
By Michael G. Akritas, I. Van Keilegom. 2001
215 citations recorded by the source corpus.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/2dccd42c6d9f3beceb9b4be909cf2884a23016f0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
- Wenceslao González-Manteiga
- Rosa M. Crujeiras
- Juan Carlos Pardo-Fernández
- César Sánchez Sellero
- Wenceslao González Manteiga
- Sam Efromovich
- I. Van Keilegom
- Natalie Neumeyer
Citations in the corpus
- Nonparametric estimation of distributional policy effects (2010, unknown): “and Serfling (1988) or Akritas and Van Keilegom (2001) for (i) and (iii).”
- An updated review of Goodness-of-Fit tests for regression models (2013, methodology): “2.2 and 2.3 to these general contexts (see Van Keilegom et al. 2008b).”
- Goodness-of-fit tests in parametric regression based on the estimation of the error distribution (2008, methodology): “This estimator has been proposed and studied by Akritas and Van Keilegom (2001) .”
- Testing for the equality of k regression curves (2007, methodology): “and proofs from Akritas and Van Keilegom (2001) .”
- Estimation of the density of regression errors (2005, background): “At the same time, there exists a vast literature devoted to density estimation based on direct observations and to estimation of functionals of the error density; see [2, 14, 34, 37] and [31] where further references can be found.”
- Estimation of Semiparametric Models When the Criterion Function is Not Smooth (2002, unknown): “See Lemma 1 in Akritas and Van Keilegom (2001) for the special case of indicator functions.”