Interval data
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Gravity Estimations with Interval Data: Revisiting the Impact of Free Trade Agreements Open
We challenge the common practice of estimating gravity equations with interval or averaged data in order to capture dynamic‐adjustment effects to trade‐policy changes. Instead, we point to a series of advantages of using consecutive‐year d…
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Authors’ response: Estimating the generation interval for COVID-19 based on symptom onset data Open
To the editor: We are grateful for the comments provided by S. Bacallado, Q. Zhao and N. Ju [1]. With this reply we wish to clarify the concerns that were raised and provide some more insights. Assumption of independence between incubation…
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Serial Interval and Generation Interval for Imported and Local Infectors, Respectively, Estimated Using Reported Contact-Tracing Data of COVID-19 in China Open
The emerging virus, COVID-19, has caused a massive outbreak worldwide. Based on the publicly available contact-tracing data, we identified 509 transmission chains from 20 provinces in China and estimated the serial interval (SI) and genera…
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Trisectional fuzzy trapezoidal approach to optimize interval data based transportation problem Open
This research article puts forward a combination of two new thoughts to solve interval data based transportation problems (IBTPs). Firstly IBTP is converted to fuzzy transportation problem using trisectional approach and secondly a newly p…
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Estimating the serial interval of the novel coronavirus disease (COVID-19): A statistical analysis using the public data in Hong Kong from January 16 to February 15, 2020 Open
Background : The emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a large outbreak of novel coronavirus disease (COVID-19) in Wuhan, China since December 2019. As of February 15, there were 56 COVID-…
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Merging decision-making units with interval data Open
This paper deals with the problem of merging units with interval data. There are two important problems in the merging units. Estimation of the inherited inputs/outputs of the merged unit from merging units is the first problem while the i…
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Augmented Interval List: a novel data structure for efficient genomic interval search Open
Motivation Genomic data is frequently stored as segments or intervals. Because this data type is so common, interval-based comparisons are fundamental to genomic analysis. As the volume of available genomic data grows, developing efficient…
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Fault Detection and Isolation Using Interval Principal Component Analysis Methods Open
Principal component analysis (PCA) is a commonly used approach to process monitoring. However, it has been developed for singleton variables. Whereas, in many real life cases, this leads to a severe loss of information, this can be overcom…
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Interval-Valued Intuitionistic Fuzzy Synthetic Measure (I-VIFSM) Based on Hellwig’s Approach in the Analysis of Survey Data Open
Several complex phenomena are measured with the use of tools in the form of a questionnaire where the values of criteria are assessed by the respondents using ordinal scales. Therefore, a special method of construction of synthetic measure…
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A support vector machine-based cure rate model for interval censored data Open
The mixture cure rate model is the most commonly used cure rate model in the literature. In the context of mixture cure rate model, the standard approach to model the effect of covariates on the cured or uncured probability is to use a log…
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A partial backlogging inventory model for deteriorating items with time-varying demand and holding cost: An interval number approach Open
This paper proposes a differential equation inventory model that incorporates partial backlogging and deterioration. Holding cost and demand rate are time dependent. Shortages are allowed and assumed to be partially backlogged. Two version…
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Feature Selection for Interval-Valued Data Based on D-S Evidence Theory Open
Feature selection is one basic and critical technology for data mining, especially in current “big data era”. Rough set theory (RST) is sensitive to noise in feature selection due to the strict condition of equivalence relati…
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Data-Driven Interval Type-2 Fuzzy Inference System Based on the Interval Type-2 Distending Function Open
Fuzzy type-2 modeling techniques are increasingly being used to model uncertain dynamical systems. However, some challenges arise when applying the existing techniques. These are: 1) A large number of rules are required to complete cover t…
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A Novel Neural Network-Based Multiobjective Evolution Lower Upper Bound Estimation Method for Electricity Load Interval Forecast Open
Currently, an interval prediction model, lower and upper bounds estimation (LUBE) which constructs the prediction intervals (PIs) by using the double outputs of the neural network (NN) is growing popular. However, existing LUBE researches …
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Estimating the serial interval of the novel coronavirus disease (COVID-19): A statistical analysis using the public data in Hong Kong from January 16 to February 15, 2020 Open
Background: The emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a large outbreak of novel coronavirus disease (COVID-19) in Wuhan, China since December 2019. As of February 15, there were 56 COVID-1…
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Improving medical decisions under incomplete data using interval–valued fuzzy aggregation Open
We state a problem concerning how to make an effective and proper decision in the presence of data incompleteness.As an example we consider a medical diagnostic system where the problem of missing data is commonly encountered.We propose an…
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Instrumental variable estimation of complier causal treatment effect with interval‐censored data Open
Assessing causal treatment effect on a time‐to‐event outcome is of key interest in many scientific investigations. Instrumental variable (IV) is a useful tool to mitigate the impact of endogenous treatment selection to attain unbiased esti…
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Dichotomized Incenter Fuzzy Triangular Ranking Approach to Optimize Interval Data Based Transportation Problem Open
This research article discusses the problems having flexible demand, supply and cost in range referred as interval data based transportation problems and these cannot be solved directly using available methods. The uncertainty associated w…
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Regression models for interval censored data using parametric pseudo-observations Open
Background Time-to-event data that is subject to interval censoring is common in the practice of medical research and versatile statistical methods for estimating associations in such settings have been limited. For right censored data, no…
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Prediction Interval Identification Using Interval Type-2 Fuzzy Logic Systems: Lake Water Level Prediction Using Remote Sensing Data Open
This paper presents a novel approach to identify the prediction interval associated with data using interval type-2 fuzzy logic systems with support vector regression. For such a purpose, a constrained quadratic objective function is defin…
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Profile Likelihood Estimation of the Correlation Coefficient in the Presence of Left, Right or Interval Censoring and Missing Data Open
We discuss implementation of a profile likelihood method for estimating a Pearson correlation coefficient from bivariate data with censoring and/or missing values.The method is implemented in an R package clikcorr which calculates maximum …
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Neural Network on Interval-Censored Data with Application to the Prediction of Alzheimer's Disease Open
Alzheimer's disease (AD) is a progressive and polygenic disorder that affects millions of individuals each year. Given that there have been few effective treatments yet for AD, it is highly desirable to develop an accurate model to predict…
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Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach Open
This paper exposes the existing problems for optimal industrial preventive maintenance intervals when decisions are made with right-censored data obtained from a network of sensors or other sources. A methodology based on the use of the z …
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Probabilistic clustering of interval data Open
In this paper we address the problem of clustering interval data, adopting a model-based approach. To this purpose, parametric models for interval-valued variables are used which consider configurations for the variance-covariance matrix t…
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Assessment of airside aerodrome infrastructure by SAW method with weights from Shannon's interval entropy Open
Multi-criteria decision support (MCDM) methods are widely used in many areas of science. This applies to economic, social and technical sciences. Implementing activities at the strategic, tactical or operational level requires appropriate …
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Neural Network Prediction Interval Based on Joint Supervision Open
In this paper, a new prediction interval model based on a joint supervision loss function for capturing the uncertainties associated with the modeled phenomenon is described. This model provides the upper and lower bounds of the predicted …
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Enhance the Uncertainty Modeling Ability of Fuzzy Grey Cognitive Maps by General Grey Number Open
In real-life systems, people cannot get precise data. The data are represented in the forms of interval or multiple intervals in many cases. Most intelligent algorithms are designed for precise data in algorithm research. People always use…
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Estimating the serial interval of the novel coronavirus disease (COVID-19): A statistical analysis using the public data in Hong Kong from January 16 to February 15, 2020 Open
Background: The emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a large outbreak of novel coronavirus disease (COVID-19) in Wuhan, China since December 2019. As of February 15, there were 56 COVID-1…
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Two-Stage Network DEA Model Under Interval Data Open
The main goal of this paper is to propose interval network data envelopment analysis (INDEA) model for performance evaluation of network decision making units (DMUs) with two stage network structure under data uncertainty.It should be expl…
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On some properties of Cronbach’s α coefficient for interval-valued data in questionnaires Open
Along recent years, interval-valued rating scales have been considered as an alternative to traditional single-point psychometric tools for human evaluations, such as Likert-type or visual analogue scales. More concretely, in answering to …