KOTLARSKI: Stata module to execute deconvolution kernel density estimation and produce a robust construction of its uniform confidence band

Kengo Kato (), Yuya Sasaki and Takuya Ura ()
Additional contact information
Kengo Kato: Cornell University
Takuya Ura: University of California, Davis

Statistical Software Components from Boston College Department of Economics

Abstract: kotlarski executes deconvolution kernel density estimation and a robust construction of its uniform confidence band based on Kato, Sasaki, and Ura (Quantitative Economics, 2021). The command requires as input two measurements, x1 and x2, of the unobserved latent variable x with classical measurement errors, e1 = x1 - x and e2 = x2 - x, respectively. The output consists of a deconvolution kernel density estimate of f(x) and their uniform confidence band over a domain of x.

Language: Stata
Requires: Stata version 14.2
Keywords: deconvolution; kernel density; confidence band; measurement error (search for similar items in EconPapers)
Date: 2021-01-15, Revised 2021-11-17
Note: This module should be installed from within Stata by typing "ssc install kotlarski". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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http://fmwww.bc.edu/repec/bocode/k/kotlarski.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/k/kotlarski.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/k/kotlarski_example_1982_1983.dta sample data file (application/x-stata)

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