Adjusting a subject-specific time of event in longitudinal studies

2019 ◽  
Vol 29 (7) ◽  
pp. 1787-1798
Author(s):  
Hyunkeun Ryan Cho ◽  
Seonjin Kim ◽  
Myung Hee Lee
Keyword(s):  
Goodness Of Fit ◽  
Real Life ◽  
Model Parameters ◽  
Specific Time ◽  
Goodness Of Fit Test ◽  
Proposed Model ◽  
Subject Specific ◽  
The Subject ◽  
The Mean ◽  
Over Time

Biomedical studies often involve an event that occurs to individuals at different times and has a significant influence on individual trajectories of response variables over time. We propose a statistical model to capture the mean trajectory alteration caused by not only the occurrence of the event but also the subject-specific time of the event. The proposed model provides a post-event mean trajectory smoothly connected with the pre-event mean trajectory by allowing the model parameters associated with the post-event mean trajectory to vary over time of the event. A goodness-of-fit test is considered to investigate how well the proposed model is fit to the data. Hypothesis tests are also developed to assess the influence of the subject-specific time of event on the mean trajectory. Theoretical and simulation studies confirm that the proposed tests choose the correctly specified model consistently and examine the effect of the subject-specific time of event successfully. The proposed model and tests are also illustrated by the analysis of two real-life data from a biomarker study for HIV patients along with their own time of treatment initiation and a body fatness study in girls with different age of menarche.

Semiparametric Inference for Proportional Mean Past Life Model

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Z. Mansourvar ◽  
M. Asadi
Keyword(s):  
Goodness Of Fit ◽  
Asymptotic Properties ◽  
Model Parameters ◽  
Goodness Of Fit Test ◽  
Data Set ◽  
Semiparametric Inference ◽  
Expected Time ◽  
Life Model ◽  
Past Life ◽  
The Mean

Abstract The mean past lifetime provides the expected time elapsed since the failure of a subject given that he/she has failed before the time of observation. In this paper, we propose the proportional mean past lifetime model to study the association between the mean past lifetime function and potential regression covariates. In the presence of left censoring, martingale estimating equations are developed to estimate the model parameters, and the asymptotic properties of the resulting estimators are studied. To assess the adequacy of the model, a goodness of fit test is also investigated. The proposed method is evaluated via simulation studies and further applied to a data set.

STORYTELLING AND MEANING RECONSTRUCTION: A METAPHORICAL PERSPECTIVE

2016 ◽  
Vol 24 (2) ◽  
pp. 159-169
Author(s):  
M L Mojapelo
Keyword(s):  
Personal Development ◽  
Real Life ◽  
Human Existence ◽  
Meaning Reconstruction ◽  
Changing Patterns ◽  
The Subject ◽  
Changes Over Time ◽  
Over Time

Storytelling consists of an interaction between a narrator and a listener, both of whom assign meaning to the story as a whole and its component parts. The meaning assigned to the narrative changes over time under the influence of the recipient‟s changing precepts and perceptions which seem to be simplistic in infancy and more nuanced with age. It becomes more philosophical in that themes touching on the more profound questions of human existence tend to become more prominently discernible as the subject moves into the more reflective or summative phases of his or her existence. The aim of this article is to demonstrate the metaphorical character of a story, as reflected in changing patterns of meaning assigned to the narrative in the course of the subjective receiver‟s passage through the various stages of life. This was done by analysing meaning, from a particular storytelling session, at different stages of a listener‟s personal development. Meaning starts as literal and evolves through re-interpretation to abstract and deeper levels towards application in real life.

A robust possibilistic programming model for production-routing problem in a three-echelon supply chain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Ali Beheshtinia ◽  
Narjes Salmabadi ◽  
Somaye Rahimi
Keyword(s):  
Supply Chain ◽  
Real Life ◽  
Model Parameters ◽  
Pickup And Delivery ◽  
Distribution Centers ◽  
Routing Problem ◽  
Remarkable Feature ◽  
Content Type ◽  
Proposed Model ◽  
Production Routing

Purpose This paper aims to provide an integrated production-routing model in a three-echelon supply chain containing a two-layer transportation system to minimize the total costs of production, transportation, inventory holding and expired drugs treatment. In the proposed problem, some specifications such as multisite manufacturing, simultaneous pickup and delivery and uncertainty in parameters are considered. Design/methodology/approach At first, a mathematical model has been proposed for the problem. Then, one possibilistic model and one robust possibilistic model equivalent to the initial model are provided regarding the uncertain nature of the model parameters and the inaccessibility of their probability function. Finally, the performance of the proposed model is evaluated using the real data collected from a pharmaceutical production center in Iran. The results reveal the proper performance of the proposed models. Findings The results obtained from applying the proposed model to a real-life production center indicated that the number of expired drugs has decreased because of using this model, also the costs of the system were reduced owing to integrating simultaneous drug pickup and delivery operations. Moreover, regarding the results of simulations, the robust possibilistic model had the best performance among the proposed models. Originality/value This research considers a two-layer vehicle routing in a production-routing problem with inventory planning. Moreover, multisite manufacturing, simultaneous pickup of the expired drugs and delivery of the drugs to the distribution centers are considered. Providing a robust possibilistic model for tackling the uncertainty in demand, costs, production capacity and drug expiration costs is considered as another remarkable feature of the proposed model.

scholarly journals Learning Personalized Itemset Mapping for Cross-Domain Recommendation

2020 ◽  
Author(s):  
Yinan Zhang ◽  
Yong Liu ◽  
Peng Han ◽  
Chunyan Miao ◽  
Lizhen Cui ◽  
...  
Keyword(s):  
Single Domain ◽  
Model Parameters ◽  
The Real ◽  
Cross Domain ◽  
Proposed Model ◽  
Latent Space ◽  
Learning Parameter ◽  
Generation Procedure ◽  
Over Time

Cross-domain recommendation methods usually transfer knowledge across different domains implicitly, by sharing model parameters or learning parameter mappings in the latent space. Differing from previous studies, this paper focuses on learning explicit mapping between a user's behaviors (i.e. interaction itemsets) in different domains during the same temporal period. In this paper, we propose a novel deep cross-domain recommendation model, called Cycle Generation Networks (CGN). Specifically, CGN employs two generators to construct the dual-direction personalized itemset mapping between a user's behaviors in two different domains over time. The generators are learned by optimizing the distance between the generated itemset and the real interacted itemset, as well as the cycle-consistent loss defined based on the dual-direction generation procedure. We have performed extensive experiments on real datasets to demonstrate the effectiveness of the proposed model, comparing with existing single-domain and cross-domain recommendation methods.

scholarly journals Consistency Bands for the Mean Excess Function and Application to Graphical Goodness-of-fit Test for Financial Data

2016 ◽  
Vol 8 (1) ◽  
pp. 42
Author(s):  
Amadou Diadie Ba ◽  
El Hadj Deme ◽  
Cheikh Tidiane Seck ◽  
Gane Samb Lo
Keyword(s):  
Goodness Of Fit ◽  
Empirical Processes ◽  
Financial Data ◽  
Generalized Hyperbolic Distribution ◽  
Goodness Of Fit Test ◽  
Excess Function ◽  
Monthly Data ◽  
Hyperbolic Distribution ◽  
Mean Excess Function ◽  
The Mean

<p>In this paper, we use the modern setting of functional empirical processes and recent techniques on uniform estimation for non parametric objects to derive consistency bands for the mean excess function in the i.i.d. case. We apply our results for modelling Dow Jones data to see how good the Generalized hyperbolic distribution fits monthly data.</p>

scholarly journals A New Extended Two-Parameter Distribution: Properties, Estimation Methods, and Applications in Medicine and Geology

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1578 ◽  
Author(s):  
Hazem Al-Mofleh ◽  
Ahmed Z. Afify ◽  
Noor Akma Ibrahim
Keyword(s):  
Estimation Method ◽  
Estimation Methods ◽  
Parameter Distribution ◽  
Model Parameters ◽  
Unknown Parameters ◽  
Proposed Model ◽  
Rate Functions ◽  
The Mean ◽  
Modeling Data ◽  
Two Parameter

In this paper, a new two-parameter generalized Ramos–Louzada distribution is proposed. The proposed model provides more flexibility in modeling data with increasing, decreasing, J-shaped, and reversed-J shaped hazard rate functions. Several statistical properties of the model were derived. The unknown parameters of the new distribution were explored using eight frequentist estimation approaches. These approaches are important for developing guidelines to choose the best method of estimation for the model parameters, which would be of great interest to practitioners and applied statisticians. Detailed numerical simulations are presented to examine the bias and the mean square error of the proposed estimators. The best estimation method and ordering performance of the estimators were determined using the partial and overall ranks of all estimation methods for various parameter combinations. The performance of the proposed distribution is illustrated using two real datasets from the fields of medicine and geology, and both datasets show that the new model is more appropriate as compared to the Marshall–Olkin exponential, exponentiated exponential, beta exponential, gamma, Poisson–Lomax, Lindley geometric, generalized Lindley, and Lindley distributions, among others.

A new generalized version of Log-logistic distribution with applications in medical sciences and other applied fields

2018 ◽  
Vol 09 (05) ◽  
pp. 1850043
Author(s):  
Bilal Ahmad Para ◽  
Tariq Rashid Jan
Keyword(s):  
Real Life ◽  
Logistic Distribution ◽  
Model Parameters ◽  
Medical Sciences ◽  
Real Life Data ◽  
Proposed Model ◽  
Asymptotic Confidence Intervals ◽  
Mc Simulation ◽  
Robust Measures ◽  
Applied Fields

In this paper, we studied a two-parameter transmuted model of Log-logistic distribution (LLD) using the quadratic rank transmutation map technique studied by Shaw and Buckley1 as a new survival model in medical sciences and other applied fields. Statistical properties of Transmuted LLD (TLLD) are discussed comprehensively. Robust measures of skewness and kurtosis of the proposed model have also been discussed along with graphical overview. The estimation of the model parameters is performed by Maximum Likelihood (ML) method followed by a Monte Carlo (MC) simulation procedure to investigate the performance of the ML estimators and the asymptotic confidence intervals of the parameters. Applications of the proposed model to real-life data are also presented.

Game Theoretical Approach to Model Decision Making for Merging Maneuvers at Freeway On-Ramps

2017 ◽  
Vol 2623 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Kyungwon Kang ◽  
Hesham A. Rakha
Keyword(s):  
Decision Making ◽  
Theoretical Approach ◽  
Model Parameters ◽  
Decision Making Process ◽  
Optimization Approach ◽  
Data Set ◽  
Deliberation Process ◽  
Proposed Model ◽  
Game Theoretical Approach ◽  
The Subject

Drivers of merging vehicles decide when to merge by considering surrounding vehicles in adjacent lanes in their deliberation process. Conflicts between drivers of the subject vehicles (i.e., merging vehicles) in an auxiliary lane and lag vehicles in the adjacent lane are typical near freeway on-ramps. This paper models a decision-making process for merging maneuvers that uses a game theoretical approach. The proposed model is based on the noncooperative decision making of two players, that is, drivers of the subject and lag vehicles, without consideration of advanced communication technologies. In the decision-making process, the drivers of the subject vehicles elect to accept gaps, and drivers of lag vehicles either yield or block the action of the subject vehicle. Corresponding payoff functions for two players were formulated to describe their respective maneuvers. To estimate model parameters, a bi-level optimization approach was used. The next generation simulation data set was used for model calibration and validation. The data set defined the moment the game started and was modeled as a continuous sequence of games until a decision is made. The defined merging decision-making model was then validated with an independent data set. The validation results reveal that the proposed model provides considerable prediction accuracy with correct predictions 84% of the time.

scholarly journals A Cautionary Note on the Use of the Kolmogorov–Smirnov Test for Normality

2007 ◽  
Vol 135 (3) ◽  
pp. 1151-1157 ◽  
Author(s):  
Dag J. Steinskog ◽  
Dag B. Tjøstheim ◽  
Nils G. Kvamstø
Keyword(s):  
Goodness Of Fit ◽  
Small Sample ◽  
Power Comparison ◽  
Goodness Of Fit Test ◽  
Kolmogorov Smirnov ◽  
The Mean ◽  
Small Sample Problem ◽  
Tests For Normality ◽  
Test For Normality ◽  
Smirnov Test

Abstract The Kolmogorov–Smirnov goodness-of-fit test is used in many applications for testing normality in climate research. This note shows that the test usually leads to systematic and drastic errors. When the mean and the standard deviation are estimated, it is much too conservative in the sense that its p values are strongly biased upward. One may think that this is a small sample problem, but it is not. There is a correction of the Kolmogorov–Smirnov test by Lilliefors, which is in fact sometimes confused with the original Kolmogorov–Smirnov test. Both the Jarque–Bera and the Shapiro–Wilk tests for normality are good alternatives to the Kolmogorov–Smirnov test. A power comparison of eight different tests has been undertaken, favoring the Jarque–Bera and the Shapiro–Wilk tests. The Jarque–Bera and the Kolmogorov–Smirnov tests are also applied to a monthly mean dataset of geopotential height at 500 hPa. The two tests give very different results and illustrate the danger of using the Kolmogorov–Smirnov test.

A numerical prediction of flexural strength probability for NBG-18 nuclear grade graphite using strength pair model

2017 ◽  
Vol 52 (3) ◽  
pp. 204-211 ◽  
Author(s):  
Manik Bansal ◽  
Indra Vir Singh ◽  
Bhanu K Mishra ◽  
Kamal Sharma ◽  
IA Khan
Keyword(s):  
Flexural Strength ◽  
Goodness Of Fit ◽  
Numerical Data ◽  
Failure Criteria ◽  
Numerical Prediction ◽  
Nuclear Grade ◽  
Goodness Of Fit Test ◽  
Strength Data ◽  
Pair Model ◽  
Proposed Model

In this work, a strength pair model has been proposed for the numerical prediction of flexural strength probability of NBG-18 nuclear grade graphite. The input to the proposed model is a random strength pair of tensile and compressive strengths whose value is based on its probability of occurrence in the experimental data. A finite element–based deterministic numerical approach has been implemented. To account for the large difference in tensile and compressive strengths, Drucker–Prager failure criteria has been implemented. The failure envelope of the Drucker–Prager failure criteria is assumed to have uniaxial fit with Mohr–Coulomb model in the principal stress space. A total of 292 simulations with random pairs of tensile and compressive strength are performed on a three-point bend specimen to obtain a set of flexural strength data. The flexural strength data obtained through numerical simulations are fitted using normal and Weibull distributions. The flexural strength probability obtained from the proposed model is found on conservative side. A goodness-of-fit test concludes that Weibull distribution fits the numerical data better than normal distribution.

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