OALib Journal
  OALib Journal is an all-in-one open access journal (ISSN Print: 2333-9705, ISSN Online: 2333-9721). It accepts a manuscript for the peer-review processing, typesetting, publication and then allocated to one of the 322 subject areas. The article processing charge for publishing in OALib journal is Only $99. For more details, please contact service@oalib.com. Submit now
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Jun 23, 2022Open    AccessArticle

Modeling Vehicle Crash Frequency When Multicollinearity Exists in Vehicle Crash Data: Ridge Regression versus Ordinary Least Squares Linear Regression

Azad Abdulhafedh
Ridge Regression is an important statistical method in modeling vehicle crash frequency when crash data contains collinear predictors. The term multicollinearity refers to the condition in which two or more predictors are highly correlated with one another. This would make the explanatory variables become very sensitive to small changes in the model. Multicollinearity reduces the precision of the estimated coefficients, which weakens the statistical power of the regression model. Common methods ...
Open Access Library J.   Vol.9, 2022

Apr 24, 2022Open    AccessArticle

Improving GM(1,1) Model Performance Accuracy Based on the Combination of Optimized Initial and Background Values in Time Series Forecasting

Mahdi Madhi, Norizan Mohamed
The term grey forecasting model has been comprehensively utilized in numerous research arenas and discovered valid outcomes. Nevertheless, the model possesses certain possible problems that necessitate improvement. It has been proven that, part of the foremost issues distressing the prediction accurateness of the model are initial and background values. Henceforth, a new modified GM(1,1) model through the combination of optimized initial value and background value has been recommended in this st...
Open Access Library J.   Vol.9, 2022

Feb 18, 2022Open    AccessArticle

Comparison between Common Statistical Modeling Techniques Used in Research, Including: Discriminant Analysis vs Logistic Regression, Ridge Regression vs LASSO, and Decision Tree vs Random Forest

Azad Abdulhafedh
Statistical techniques are important tools in modeling research work. However, there could be misleading outcomes if sufficient care is undermined in choosing the right approach. Employing the correct analysis in any research work needs deep knowledge on the differences between these tools. Incorrect selection of the modeling technique would create serious problems during the interpretation of the findings and could affect the conclusion of the study. Each technique has its own assumptions and p...
Open Access Library J.   Vol.9, 2022

Jan 29, 2022Open    AccessArticle

Incorporating Multiple Linear Regression in Predicting the House Prices Using a Big Real Estate Dataset with 80 Independent Variables

Azad Abdulhafedh
This paper uses a multiple linear regression analysis to predict the final price of a house in a big real estate dataset. The data describes the sale of individual properties, various features, and details of each home in Ames, Iowa, USA from 2006 to 2010. The dataset comprises of 80 explanatory variables which include 23 nominal, 23 ordinal, 14 discrete, and 20 continuous variables. The goal was to use the training data to predict the sale prices of the houses in the testing data. The most impo...
Open Access Library J.   Vol.9, 2022

Feb 26, 2021Open    AccessArticle

The Behaviour of the Dispersion Matrix of the Information Matrix Test under the Wrong Logistic Regression Model

Nuri H. Salem Badi
The Information Matrix Tests (IMT) considers as one of the important global goodness of fit test. The IMT provides a unified framework for specification goodness of fit tests for a wide variety of distribution, multivariate or univariate, discrete or continuous. Many researchers discussed the IMT in cases of the outcome covariate is a continuous variable which reported it has reasonable behaviour. This article considers using IMT as a goodness of fit test for the logistic regression mode, to inv...
Open Access Library J.   Vol.8, 2021

Jan 22, 2021Open    AccessArticle

Mathematical Procedures for the Non-Coplanar Tangential Transfers between Circular Orbits

A. A. Alqarni
To transfer a satellite or a spacecraft from a low parking orbit to another orbit requires one of the many orbital transfers. These orbital transfers need to determine some orbital elements of the initial and final orbits as perigee and apogee distances. The transfers compete to achieve the transition with minimal consumption of energy, transfer time, as well as the highest accuracy of transition. In the present research, certain mathematical procedures implementable with the help of computers w...
Open Access Library J.   Vol.8, 2021

Sep 16, 2020Open    AccessArticle

Outlier Detection and Effects on Modeling

Christopher O. Arimie, Emmanuel O. Biu, Maxwell A. Ijomah
In this work, a comprehensive framework for traditional outlier detection techniques based on simple and multiple linear regression models was studied. Two data sets were used for the illustration and evaluation of each class of outlier detection techniques (analytical and graphical methods). Outlier detection aims at identifying such outlier in order to improve the analytic of data and suitable model built. Furthermore, comparisons of the different methods were done to highlight the advantages,...
Open Access Library J.   Vol.7, 2020

Jul 31, 2020Open    AccessArticle

New Anomaly at Low Temperature for Heat Capacity

Sonia Bouzgarrou
In this paper, we present a theoretical investigation as a function of temperature of a critical anomaly find in InAlAs hetero-structure of two-dimensional electron gas. This study has shown the presence of a large and continuous anomaly. This anomaly is explained through a theory based on the general assumption. The present theoretical research is based essentially on the characteristic of specific heat capacity extending over a large temperature, but we underline a good agreement with results ...
Open Access Library J.   Vol.7, 2020

Jul 13, 2020Open    AccessArticle

Additive Decomposition with Arima Model Forecasts When the Trend Component Is Quadratic

Biu O. Emmanuel, Dennis Enegesele, C. O. Arimie
This paper demonstrates the use of Buys-Ballot table for identification of decomposition model using graphical method, when the trend cycle component is quadratic. A suitable ARIMA model was fitted, and was used for forecasting. Using the Buys-Ballot techniques, the column means, variances and standard deviation were estimated for the model identification. The additive model had no seasonal effect but, the multiplicative model had seasonal effect. The result of the illustrative example using the...
Open Access Library J.   Vol.7, 2020

May 29, 2020Open    AccessArticle

Octave Analysis of Logistic Growth Model for Pig Pen: Its Economic Viability

I. S. S. Abang, O. N. Nze, O. A. Oriola, I. S. Amasiatu
Pig pen is fast becoming a very lucrative system of farming in Nigeria, most especially in the South-Eastern region of the country. This form of animal farming is very cost effective and does not need much training before someone ventures into it, as pigs are a very special breed of animals that can eat almost any kind of food, and they do not fall sick easily when compared with chicken poultry or fish poultry business. This paper also discussed how swine breeding could help in addressing enviro...
Open Access Library J.   Vol.7, 2020


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