scholarly journals Identification in a fully nonparametric transformation model with heteroscedasticity

2021 ◽  
Vol 170 ◽  
pp. 109018
Author(s):  
Nick Kloodt
Keyword(s):  
Transformation Model ◽  
Nonparametric Transformation

On semiparametric modelling, estimation and inference for survival data subject to dependent censoring

Biometrika ◽  
2020 ◽  
Author(s):  
N W Deresa ◽  
I Van Keilegom
Keyword(s):  
Linear Model ◽  
Survival Data ◽  
Estimation Method ◽  
Bivariate Normal Distribution ◽  
Dependent Censoring ◽  
Transformation Model ◽  
Model Parameters ◽  
Finite Sample ◽  
Asymptotically Normal ◽  
Nonparametric Transformation

Abstract When modelling survival data, it is common to assume that the survival time T is conditionally independent of the censoring time C given a set of covariates. However, there are numerous situations in which this assumption is not realistic. The goal of this paper is therefore to develop a semiparametric normal transformation model, which assumes that after a proper nonparametric monotone transformation, the vector (T, C) follows a linear model, and the vector of errors in this bivariate linear model follows a standard bivariate normal distribution with possibly non-diagonal covariance matrix. We show that this semiparametric model is identifiable, and propose estimators of the nonparametric transformation, the regression coefficients and the correlation between the error terms. It is shown that the estimators of the model parameters and the transformation are consistent and asymptotically normal. We also assess the finite sample performance of the proposed method by comparing it with an estimation method under a fully parametric model. Finally, our method is illustrated using data from the AIDS Clinical Trial Group 175 study.

Human Rights in a Neoliberal World

2017 ◽  
Author(s):  
Madeline Baer
Keyword(s):  
Human Rights ◽  
Social Transformation ◽  
Water Policy ◽  
Empirical Work ◽  
Transformation Model ◽  
Central Research ◽  
Transformative Change ◽  
Human Right ◽  
Regulatory Frameworks ◽  
Negative Effect

Chapter 2 presents the central research questions that drive the theoretical and empirical work of the book, outlines the “moments of social transformation” model used for analyzing human rights realization, and positions the book in relation to theoretical and contemporary policy debates. The chapter synthesizes the literatures on socioeconomic human rights fulfillment and the human right to water and sanitation. It introduces two key elements for implementing human rights: political will and state capacity, as well as some obstacles to rights realization, including lack of strong regulatory frameworks and accountability mechanisms. The chapter explores the tensions between markets and rights, finding that neoliberal approaches to water policy have a negative effect on rights fulfillment by weakening the state’s role, and it engages with critiques that the human rights frame is too narrow and vague to facilitate transformative change in the water sector.

scholarly journals Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3425
Author(s):  
Huanping Li ◽  
Jian Wang ◽  
Guopeng Bai ◽  
Xiaowei Hu
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Flow Model ◽  
Road Traffic ◽  
Autonomous Vehicle ◽  
Transformation Model ◽  
Hydrodynamic Theory ◽  
Traffic Flow Model ◽  
Traffic System ◽  
The Stability

In order to explore the changes that autonomous vehicles would bring to the current traffic system, we analyze the car-following behavior of different traffic scenarios based on an anti-collision theory and establish a traffic flow model with an arbitrary proportion (p) of autonomous vehicles. Using calculus and difference methods, a speed transformation model is established which could make the autonomous/human-driven vehicles maintain synchronized speed changes. Based on multi-hydrodynamic theory, a mixed traffic flow model capable of numerical calculation is established to predict the changes in traffic flow under different proportions of autonomous vehicles, then obtain the redistribution characteristics of traffic flow. Results show that the reaction time of autonomous vehicles has a decisive influence on traffic capacity; the q-k curve for mixed human/autonomous traffic remains in the region between the q-k curves for 100% human and 100% autonomous traffic; the participation of autonomous vehicles won’t bring essential changes to road traffic parameters; the speed-following transformation model minimizes the safety distance and provides a reference for the bottom program design of autonomous vehicles. In general, the research could not only optimize the stability of transportation system operation but also save road resources.

scholarly journals Assessing Digital Transformation in Universities

2021 ◽  
Vol 13 (2) ◽  
pp. 52
Author(s):  
Guillermo Rodríguez-Abitia ◽  
Graciela Bribiesca-Correa
Keyword(s):  
Business Models ◽  
Digital Transformation ◽  
Transformation Model ◽  
Educational Institutions ◽  
Maturity Level ◽  
Network Applications ◽  
Innovative Products ◽  
Education Market ◽  
Transformation Processes ◽  
Degree Of Innovation

Industry 4.0 and Society 5.0 are reshaping the way organizations function and interact with the communities they serve. The massive penetration of computer and network applications forces organizations to digitalize their processes and provide innovative products, services, and business models. The education market is suffering changes as well, but universities seem slow to react. This paper proposes the application of an integrated digital transformation model to assess the maturity level that educational institutions have in their digital transformation processes and compares them to other industries. Particular considerations to address when using the model for higher-education institutions are discussed. Our results show that universities fall behind other sectors, probably due to a lack of effective leadership and changes in culture. This is complemented negatively by an insufficient degree of innovation and financial support.

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