Results 81 to 90 of about 98,530 (284)

Can outsourcing pest and disease control help reduce pesticide expenditure? Evidence from rice farmers

Agribusiness, EarlyView.
Abstract Outsourcing pest and disease control (PDC) has grown rapidly worldwide, especially in developing countries. Although numerous studies have investigated various advantages of outsourcing PDC, little is known about its impact on pesticide expenditure.
Pengcheng Wang, Wanglin Ma, Mengling Diao   +2 more
wiley   +1 more source

Exp-Kumaraswamy Distributions: Some Properties and Applications [PDF]

Journal of Sciences, Islamic Republic of Iran, 2015
In this paper, we propose and study exp-kumaraswamy distribution. Some of its properties  are derived, including the density function, hazard rate function, quantile function, moments,  skewness  and kurtosis.
Z. Javanshiri, A. Habibi Rad, N.R. Arghami   +2 more
doaj  

Quantile calculus and censored regression

, 2010
Quantile regression has been advocated in survival analysis to assess evolving covariate effects. However, challenges arise when the censoring time is not always observed and may be covariate-dependent, particularly in the presence of continuously ...
Huang, Yijian
core   +1 more source

Topological Properties of International Commodity Market: How Uncertainty Affects the Linkages?

Agribusiness, EarlyView.
ABSTRACT The study aims to explore the network topology of the international commodity market by examining the interconnections among 21 commodity futures across various categories, including energy, precious and industrial metals, and agriculture. We analyze the market structure of these commodity futures under both low and high uncertainty conditions
Ibrahim Yagli, Bayram Deviren
wiley   +1 more source

A new flexible distribution: Statistical inference with application

AIP Advances
A flexible distribution for the analysis of bounded data is proposed. The new model is generalized through the transmuted approach, and the resultant model is named “transmuted modified Lehmann-type II distribution.” A comprehensive analysis of key ...
Muhammad Ahsan-ul-Haq, Muhammad Umar Farooq, M. Nagy, A. H. Mansi, Alexis Habineza, Waleed Marzouk   +5 more
doaj   +1 more source

Classes of Ordinary Differential Equations Obtained for the Probability Functions of Harris Extended Exponential Distribution [PDF]

, 2017
In this paper, the differential calculus was used to obtain some classes of ordinary differential equations (ODE) for the probability density function, quantile function, survival function, inverse survival function and hazard function of the Harris ...
Adamu, M. O., Okagbue, H. I., Owoloko, E. A., Suleiman, Esivue A.   +3 more
core  

Assessing the Impact of Promotions on Consumer Purchasing Behavior During Crises

Agribusiness, EarlyView.
ABSTRACT Understanding how households modify their food expenditure decisions during times of crisis is essential because consumer purchasing behavior frequently changes during these times. This study looks at these behavioral shifts during the COVID‐19 pandemic, concentrating on how price sensitivity and response to sales promotions changed over the ...
Wafa Mehaba, José María Gil
wiley   +1 more source

The Log-logistic Weibull Distribution with Applications to Lifetime Data

Austrian Journal of Statistics, 2016
In this paper, a new generalized distribution called the log-logistic Weibull (LLoGW) distribution is developed and presented. This dis- tribution contain the log-logistic Rayleigh (LLoGR), log-logistic expo- nential (LLoGE) and log-logistic (LLoG ...
Broderick Oluyede, Susan Foya, Gayan Warahena-Liyanage, Shujiao Huang   +3 more
doaj   +1 more source

Application of a simple nonparametric conditional quantile function estimator in unemployment duration analysis [PDF]

We consider an extension of conventional univariate Kaplan-Meier type estimators for the hazard rate and the survivor function to multivariate censored data with a censored random regressor.
Wichert, Laura, Wilke, Ralf A.
core  

RPSLearner: A Novel Approach Based on Random Projection and Deep Stacking Learning for Categorizing Non‐Small Cell Lung Cancer

Advanced Intelligent Systems, EarlyView.
Identifying non‐small cell lung cancer (NSCLC) subtypes is essential for precision cancer treatment. Conventional methods are laborious, or time‐consuming. To address these concerns, RPSLearner is proposed, which combines random projection and stacking ensemble learning for accurate NSCLC subtyping. RPSLearner outperforms state‐of‐the‐art approaches in
Xinchao Wu, Jieqiong Wang, Shibiao Wan
wiley   +1 more source