EconBiz - Find Economic Literature
    • Logout
    • Change account settings
  • A-Z
  • Beta
  • About EconBiz
  • News
  • Thesaurus (STW)
  • Academic Skills
  • Help
  •  My account 
    • Logout
    • Change account settings
  • Login
EconBiz - Find Economic Literature
Publications Events
Search options
Advanced Search history
My EconBiz
Favorites Loans Reservations Fines
    You are here:
  • Home
  • Search: subject:"training and test samples"
Narrow search

Narrow search

Year of publication
Subject
All
generalized method of moments framework 2 instrumental variables 2 regularization 2 ridge regression 2 training and test samples 2 Betriebliches Bildungsmanagement 1 Employer-provided training 1 Estimation 1 Estimation theory 1 IV-Schätzung 1 Instrumental variables 1 Method of moments 1 Momentenmethode 1 Regression analysis 1 Regressionsanalyse 1 Sampling 1 Schätztheorie 1 Schätzung 1 Stichprobenerhebung 1
more ... less ...
Online availability
All
Free 2 CC license 1
Type of publication
All
Article 2
Type of publication (narrower categories)
All
Article 1 Article in journal 1 Aufsatz in Zeitschrift 1
Language
All
English 2
Author
All
Sengupta, Nandana 2 Sowell, Fallaw 2
Published in...
All
Econometrics 1 Econometrics : open access journal 1
Source
All
ECONIS (ZBW) 1 EconStor 1
Showing 1 - 2 of 2
Cover Image
On the asymptotic distribution of ridge regression estimators using training and test samples
Sengupta, Nandana; Sowell, Fallaw - In: Econometrics 8 (2020) 4, pp. 1-25
and test samples and becomes an estimated parameter that jointly converges with the parameters of interest. The asymptotic … regression penalty is characterized. The regularization tuning parameter is selected by splitting the observed data into training …
Persistent link: https://www.econbiz.de/10012696302
Saved in:
Cover Image
On the asymptotic distribution of ridge regression estimators using training and test samples
Sengupta, Nandana; Sowell, Fallaw - In: Econometrics : open access journal 8 (2020) 4/39, pp. 1-25
and test samples and becomes an estimated parameter that jointly converges with the parameters of interest. The asymptotic … regression penalty is characterized. The regularization tuning parameter is selected by splitting the observed data into training …
Persistent link: https://www.econbiz.de/10012312086
Saved in:
A service of the
zbw
  • Sitemap
  • Plain language
  • Accessibility
  • Contact us
  • Imprint
  • Privacy

Loading...