A Class of Regression Estimator with Cum-Dual Product Estimator as Intercept

α
N.A. Adegoke
N.A. Adegoke
σ
F.B. Adebola
F.B. Adebola
α Federal University of Technology Federal University of Technology

Send Message

To: Author

A Class of Regression Estimator with Cum-Dual Product Estimator as Intercept

Article Fingerprint

ReserarchID

7RH7O

A Class of Regression Estimator with Cum-Dual Product Estimator as Intercept Banner

AI TAKEAWAY

Connecting with the Eternal Ground
  • English
  • Afrikaans
  • Albanian
  • Amharic
  • Arabic
  • Armenian
  • Azerbaijani
  • Basque
  • Belarusian
  • Bengali
  • Bosnian
  • Bulgarian
  • Catalan
  • Cebuano
  • Chichewa
  • Chinese (Simplified)
  • Chinese (Traditional)
  • Corsican
  • Croatian
  • Czech
  • Danish
  • Dutch
  • Esperanto
  • Estonian
  • Filipino
  • Finnish
  • French
  • Frisian
  • Galician
  • Georgian
  • German
  • Greek
  • Gujarati
  • Haitian Creole
  • Hausa
  • Hawaiian
  • Hebrew
  • Hindi
  • Hmong
  • Hungarian
  • Icelandic
  • Igbo
  • Indonesian
  • Irish
  • Italian
  • Japanese
  • Javanese
  • Kannada
  • Kazakh
  • Khmer
  • Korean
  • Kurdish (Kurmanji)
  • Kyrgyz
  • Lao
  • Latin
  • Latvian
  • Lithuanian
  • Luxembourgish
  • Macedonian
  • Malagasy
  • Malay
  • Malayalam
  • Maltese
  • Maori
  • Marathi
  • Mongolian
  • Myanmar (Burmese)
  • Nepali
  • Norwegian
  • Pashto
  • Persian
  • Polish
  • Portuguese
  • Punjabi
  • Romanian
  • Russian
  • Samoan
  • Scots Gaelic
  • Serbian
  • Sesotho
  • Shona
  • Sindhi
  • Sinhala
  • Slovak
  • Slovenian
  • Somali
  • Spanish
  • Sundanese
  • Swahili
  • Swedish
  • Tajik
  • Tamil
  • Telugu
  • Thai
  • Turkish
  • Ukrainian
  • Urdu
  • Uzbek
  • Vietnamese
  • Welsh
  • Xhosa
  • Yiddish
  • Yoruba
  • Zulu

Abstract

This paper examines a class of regression estimator with cum-dual product estimator as intercept for estimating the mean of the study variable Y using auxiliary variable X. We obtained the bias and the mean square error (MSE) of the proposed estimator. We also obtained MSE of its asymptotically optimum estimator (AOE). Theoretical and numerical validation of the proposed estimator was done to show it’s superiority over the usual simple random sampling estimator and ratio estimator, product estimator, cum-dual ratio and product estimator. It was found that the asymptotic optimal value of the proposed estimator performed better than other competing estimators and performed in exactly the same way as the regression estimator, when compared with the usual simple random estimator for estimating the average sleeping hours of undergraduate students of the department of statistics,

References

4 Cites in Article
  1. T Srivenkataramana (1980). A dual to ratio estimator in sample surveys.
  2. P Sukhatme,B Sukhatme,C Sok (1984). Sampling theory of surveys with applications.
  3. P Sukhatme,B Sukhatme (1970). Sampling theory of surveys with Applications.
  4. F Yates (1960). Sampling methods in censuses and surveys.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

N.A. Adegoke. 2015. \u201cA Class of Regression Estimator with Cum-Dual Product Estimator as Intercept\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 15 (GJSFR Volume 15 Issue F3): .

Download Citation

Issue Cover
GJSFR Volume 15 Issue F3
Pg. 49- 56
Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords
Classification
GJSFR-F Classification: MSC 2010: 62J07
Version of record

v1.2

Issue date

May 4, 2015

Language
en
Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

Article Matrices
Total Views: 4322
Total Downloads: 2128
2026 Trends
Related Research

Published Article

This paper examines a class of regression estimator with cum-dual product estimator as intercept for estimating the mean of the study variable Y using auxiliary variable X. We obtained the bias and the mean square error (MSE) of the proposed estimator. We also obtained MSE of its asymptotically optimum estimator (AOE). Theoretical and numerical validation of the proposed estimator was done to show it’s superiority over the usual simple random sampling estimator and ratio estimator, product estimator, cum-dual ratio and product estimator. It was found that the asymptotic optimal value of the proposed estimator performed better than other competing estimators and performed in exactly the same way as the regression estimator, when compared with the usual simple random estimator for estimating the average sleeping hours of undergraduate students of the department of statistics,

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

A Class of Regression Estimator with Cum-Dual Product Estimator as Intercept

F.B. Adebola
F.B. Adebola
N.A. Adegoke
N.A. Adegoke Federal University of Technology

Research Journals