A proposed Penalty Method for Processing High-Dimensional Data in a Factorial Experiment "2 4" with Two Replication
| المصدر: | مجلة القادسية للعلوم الإدارية والاقتصادية |
|---|---|
| الناشر: | جامعة القادسية - كلية الادارة والاقتصاد |
| المؤلف الرئيسي: | Saleem, Wisam Wadullah (Author) |
| مؤلفين آخرين: | Jaber, Asmaa Ghalib (Co-Author) |
| المجلد/العدد: | مج24, ع3 |
| محكمة: | نعم |
| الدولة: |
العراق |
| التاريخ الميلادي: |
2022
|
| الصفحات: | 774 - 790 |
| ISSN: |
1816-9171 |
| رقم MD: | 1338882 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Two-Level Factorial Design | Regression Experiment Design | Variable Selection | Interaction | Lasso | Adaptive lasso
|
| رابط المحتوى: |
الناشر لهذه المادة لم يسمح بإتاحتها. |
| LEADER | 02326nam a22002297a 4500 | ||
|---|---|---|---|
| 001 | 2095520 | ||
| 041 | |a eng | ||
| 044 | |b العراق | ||
| 100 | |9 710244 |a Saleem, Wisam Wadullah |e Author | ||
| 245 | |a A proposed Penalty Method for Processing High-Dimensional Data in a Factorial Experiment "2 4" with Two Replication | ||
| 260 | |b جامعة القادسية - كلية الادارة والاقتصاد |c 2022 | ||
| 300 | |a 774 - 790 | ||
| 336 | |a بحوث ومقالات |b Article | ||
| 520 | |b In this paper, a method is proposed to model the mathematical model of a factorial experiment (24) applied in a complete random design suffering from high-dimensional data to a multiple regression model using the general linear model where the matrix (X) contains (81) columns and (32) rows, The columns represent the effect of the levels of each factor and the effect of the interaction between the levels of these factors in addition to the effect of the general arithmetic mean, and the rows represent the number of experiment observations (sample size), then the selection of factors and interactions of important factors using the penalty methods (Lasso, adaptive lasso) and the proposed method on the lasso adaptive weight It was compared with the methods mentioned . A simulation study are conducted to investigate the performance of the proposed method. We employed the mean square errors, R-square, Adjusted R-square and Mean absolute deviation to select the best model and the results show that the proposed method using the lasso adaptive weight variable selection performs well. | ||
| 653 | |a العمليات الإحصائية |a تحليل البيانات |a النماذج الرياضية | ||
| 692 | |b Two-Level Factorial Design |b Regression Experiment Design |b Variable Selection |b Interaction |b Lasso |b Adaptive lasso | ||
| 700 | |9 710248 |a Jaber, Asmaa Ghalib |e Co-Author | ||
| 773 | |4 الاقتصاد |4 إدارة الأعمال |6 Economics |6 Business |c 052 |e Al-Qadisiyah Journal for Administrative & Economic Sciences |f Maǧallaẗ al-qādisiyyaẗ li-l-ʻulūm al-idāriyyaẗ wa-al-iqtiṣādiyyaẗ |l 003 |m مج24, ع3 |o 0478 |s مجلة القادسية للعلوم الإدارية والاقتصادية |v 024 |x 1816-9171 | ||
| 856 | |u 0478-024-003-052.pdf | ||
| 930 | |d n |p y |q n | ||
| 995 | |a EcoLink | ||
| 999 | |c 1338882 |d 1338882 | ||
عناصر مشابهة
-
Analysis of Interaction in the Case of No Replication in a Two-Factor Experiment
بواسطة: حسن، سامية خالد منشور: (2023) -
Improved Shrinkage Method for High Dimensional Data
بواسطة: ALkumaisi, Afrah Darwish Sloom منشور: (2020) -
A Proposed Model For Data Warehouse ETL Processes
بواسطة: El-Sappagh, Shaker H. Ali منشور: (2011) -
The Minimax Concave Penalty Variable Selection Regularization Method for Regression Discontinuity Designs
بواسطة: Mohammed, Bahr Kadhim منشور: (2021) -
Investigations of Methods of Analysis of Likert-Type Scale Data In Surveys
بواسطة: Alma'mari, Afraa Awadh Salim منشور: (2013)
