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Journal articles on the topic 'Right censored observations'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

ZHANG, Bin, and Zhongsheng HUA. "Nonparametric Demand Forecasting with Right Censored Observations." Journal of Software Engineering and Applications 02, no. 04 (2009): 259–66. http://dx.doi.org/10.4236/jsea.2009.24033.

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2

Magel, Rhonda C. "Robust Estimates of Ordered Parameters with Right Censored Observations." Communications in Statistics - Simulation and Computation 19, no. 1 (1990): 207–23. http://dx.doi.org/10.1080/03610919008812853.

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3

Aydın, Dursun, Syed Ejaz Ahmed, and Ersin Yılmaz. "Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator." Entropy 23, no. 12 (2021): 1586. http://dx.doi.org/10.3390/e23121586.

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This paper focuses on the adaptive spline (A-spline) fitting of the semiparametric regression model to time series data with right-censored observations. Typically, there are two main problems that need to be solved in such a case: dealing with censored data and obtaining a proper A-spline estimator for the components of the semiparametric model. The first problem is traditionally solved by the synthetic data approach based on the Kaplan–Meier estimator. In practice, although the synthetic data technique is one of the most widely used solutions for right-censored observations, the transformed

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4

Kattumannil, Sudheesh K., Isha Dewan, and Sreelaksmi N. "Non-parametric estimation of Gini index with right censored observations." Statistics & Probability Letters 175 (August 2021): 109113. http://dx.doi.org/10.1016/j.spl.2021.109113.

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5

Zhao, Lihui, and X. Joan Hu. "Estimation with right-censored observations under a semi-Markov model." Canadian Journal of Statistics 41, no. 2 (2013): 237–56. http://dx.doi.org/10.1002/cjs.11176.

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6

Adamic, Peter, and Jenna Guse. "LOESS smoothed density estimates for multivariate survival data subject to censoring and masking." Annals of Actuarial Science 10, no. 2 (2016): 285–302. http://dx.doi.org/10.1017/s1748499516000099.

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AbstractActuaries often encounter censored and masked survival data when constructing multiple-decrement tables. In this paper, we propose estimators for the cause-specific failure time density using LOESS smoothing techniques that are employed in the presence of left-censored data, while still allowing for right-censored and exact observations, as well as masked causes of failure. The smoothing mechanism is incorporated as part of an expectation-maximisation algorithm. The proposed models are applied to a bivariate African sleeping sickness data set.

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7

Subramanian, Sundarraman. "Median regression analysis from data with left and right censored observations." Statistical Methodology 4, no. 2 (2007): 121–31. http://dx.doi.org/10.1016/j.stamet.2006.03.001.

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8

Coolen-Maturi, Tahani, Ali M. Mahnashi, and Frank P. A. Coolen. "Nonparametric Predictive Inference for Two Future Observations with Right-Censored Data." Mathematical Methods of Statistics 33, no. 4 (2024): 338–72. https://doi.org/10.3103/s1066530724700182.

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9

Ayushee, Ayushee, Narinder Kumar, and Manish Goyal. "TWO-SAMPLE TEST FOR RANDOMLY CENSORED DATA." Malaysian Journal of Science 42, no. 1 (2023): 32–41. http://dx.doi.org/10.22452/mjs.vol42no1.4.

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In this paper, a nonparametric test has been proposed for the two-sample scale problem, when sample observations are randomly right censored. The proposed test is based on the extremes of observations as an extension of commonly used Gehan’s test for two-sample problem. Critical values are obtained through simulation for various lifetime distributions at different sample sizes. Power performance for the proposed test is studied considering various distributions. On comparing with the Gehan’s test, it is found that the proposed test has more statistical power and efficiency for some special cas

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10

Yılmaz, Ersin, Syed Ejaz Ahmed, and Dursun Aydın. "A-Spline Regression for Fitting a Nonparametric Regression Function with Censored Data." Stats 3, no. 2 (2020): 120–36. http://dx.doi.org/10.3390/stats3020011.

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This paper aims to solve the problem of fitting a nonparametric regression function with right-censored data. In general, issues of censorship in the response variable are solved by synthetic data transformation based on the Kaplan–Meier estimator in the literature. In the context of synthetic data, there have been different studies on the estimation of right-censored nonparametric regression models based on smoothing splines, regression splines, kernel smoothing, local polynomials, and so on. It should be emphasized that synthetic data transformation manipulates the observations because it as

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11

Leemis, Lawrence M., and Li-Hsing Shih. "Exponential Parameter Estimation for Data Sets Containing Left and Right Censored Observations." Communications in Statistics - Simulation and Computation 18, no. 3 (1989): 1077–85. http://dx.doi.org/10.1080/03610918908812807.

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12

Zheng, Lu, and Marvin Zelen. "Urn sampling, interval censoring and proportional hazard models." Statistical Modelling 9, no. 4 (2009): 361–79. http://dx.doi.org/10.1177/1471082x0900900406.

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This paper proposes a new distribution-free statistical method for testing hypotheses about covariates for survival data having simultaneously right-, left- and interval-censored survival times. The new test is motivated by the analogue between urn sampling and the Cox’s proportional hazard models. Investigations of the significance levels and power as a function of the proportion of interval-censored observations and interval length show that the test performs well for most censoring situations encountered in practice. Simulation results also suggest that there is negligible loss of power in

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13

Péron, Julien, Maryam Idlhaj, Delphine Maucort‐Boulch, et al. "Correcting the bias of the net benefit estimator due to right‐censored observations." Biometrical Journal 63, no. 4 (2021): 893–906. http://dx.doi.org/10.1002/bimj.202000001.

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14

Lubecke, André M., and W. J. Padgett. "Nonparametric maximum penalized likelihood estimation of a density from arbitrarily right-censored observations." Communications in Statistics - Theory and Methods 14, no. 2 (1985): 257–71. http://dx.doi.org/10.1080/03610928508828910.

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15

Lee, MinJae, Mohammad H. Rahbar, and Hooshang Talebi. "A nonparametric method for assessment of interactions in a median regression model for analyzing right censored data." Statistical Methods in Medical Research 28, no. 4 (2018): 1170–87. http://dx.doi.org/10.1177/0962280217751518.

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We propose a nonparametric test for interactions when we are concerned with investigation of the simultaneous effects of two or more factors in a median regression model with right censored survival data. Our approach is developed to detect interaction in special situations, when the covariates have a finite number of levels with a limited number of observations in each level, and it allows varying levels of variance and censorship at different levels of the covariates. Through simulation studies, we compare the power of detecting an interaction between the study group variable and a covariate

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16

Abdushukurov, Abdurakhim A., Sukhrob B. Bozorov, and Dilshod R. Mansurov. "Optimal kernel density estimation by statistical modeling with random censoring of observations." Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitel'naya tekhnika i informatika, no. 67 (2024): 49–59. http://dx.doi.org/10.17223/19988605/67/6.

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The problems of nonparametric estimation of the probability of failure-free operation and the density distribution function of the operating time of some physical device are considered. Randomly right-censored observations are used. Estimates of a complex structure are constructed: multiplying, exponential, as well as power estimates and an estimate with modification. New estimates for the distribution density using the kernel method are proposed. Tables of the optimal choice of smoothing parameters obtained using statistical modeling are presented.

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17

Sadeghzadeh, Keivan, and Nasser Fard. "Variable Selection Methods for Right-Censored Time-to-Event Data with High-Dimensional Covariates." Journal of Quality and Reliability Engineering 2015 (May 10, 2015): 1–9. http://dx.doi.org/10.1155/2015/795154.

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Advancement in technology has led to greater accessibility of massive and complex data in many fields such as quality and reliability. The proper management and utilization of valuable data could significantly increase knowledge and reduce cost by preventive actions, whereas erroneous and misinterpreted data could lead to poor inference and decision making. On the other side, it has become more difficult to process the streaming high-dimensional time-to-event data in traditional application approaches, specifically in the presence of censored observations. This paper presents a multipurpose an

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18

Karadeniz, Pinar Gunel, and Ilker Ercan. "EXAMINING TESTS FOR COMPARING SURVIVAL CURVES WITH RIGHT CENSORED DATA." Statistics in Transition new series 18, no. 2 (2017): 311–28. http://dx.doi.org/10.59170/stattrans-2017-016.

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Background and objective: In survival analysis, estimating the survival probability of a population is important, but on the other hand, investigators want to compare the survival experiences of different groups. In such cases, the differences can be illustrated by drawing survival curves, but this will only give a rough idea. Since the data obtained from survival studies contains frequently censored observations some specially designed tests are required in order to compare groups statistically in terms of survival. Methods: In this study, Logrank, Gehan-Wilcoxon, Tarone-Ware, Peto-Peto, Modi

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19

SHASTRI, VASTOSHPATI, and DEEPENDRA S. PAL. "Bayesian Point Prediction for Rayleigh distribution when observations are censored to left and right." Journal of Ultra Scientist of Physical Sciences Section A 30, no. 02 (2018): 97–109. http://dx.doi.org/10.22147/jusps-a/300201.

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20

Coolen, F. P. A. "An imprecise Dirichlet model for Bayesian analysis of failure data including right-censored observations." Reliability Engineering & System Safety 56, no. 1 (1997): 61–68. http://dx.doi.org/10.1016/s0951-8320(96)00131-7.

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21

Panza, Carlos Arturo, and Jose Alberto Vargas. "Monitoring Weibull regression models with type I right-censored observations in phase II processes." Communications in Statistics - Simulation and Computation 49, no. 2 (2018): 335–54. http://dx.doi.org/10.1080/03610918.2018.1484478.

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22

Arasan, Jayanthi, and Habshah Midi. "Bootstrap Based Diagnostics for Survival Regression Model with Interval and Right-Censored Data." Austrian Journal of Statistics 52, no. 2 (2023): 66–85. http://dx.doi.org/10.17713/ajs.v52i2.1393.

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This research proposes a new approach based on the bias-corrected bootstrap harmonic mean and random imputation technique to obtain the adjusted residuals (Hboot) when a survival model is fit to right- and interval-censored data with covariates. Following that, the model adequacy and influence diagnostics based on these adjusted residuals, case deletion diagnostics, and the normal curvature are discussed. Simulation studies were conducted to assess the performance of the parameter estimate and compare the performances of the traditional Cox-Snell (CS), modified Cox-Snell (MCS) and Hboot at var

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23

Gorfine, Malka, Matan Schlesinger, and Li Hsu. "K-sample omnibus non-proportional hazards tests based on right-censored data." Statistical Methods in Medical Research 29, no. 10 (2020): 2830–50. http://dx.doi.org/10.1177/0962280220907355.

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This work presents novel and powerful tests for comparing non-proportional hazard functions, based on sample–space partitions. Right censoring introduces two major difficulties, which make the existing sample–space partition tests for uncensored data non-applicable: (i) the actual event times of censored observations are unknown and (ii) the standard permutation procedure is invalid in case the censoring distributions of the groups are unequal. We overcome these two obstacles, introduce invariant tests, and prove their consistency. Extensive simulations reveal that under non-proportional alter

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24

Colak, Ertugrul, Hulya Ozen, Busra Emir, and Setenay Oner. "Pairwise Multiple Comparison Adjustment Procedure for Survival Functions with Right-Censored Data." Computational and Mathematical Methods in Medicine 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/9270450.

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The aim of this study is to propose a new pairwise multiple comparison adjustment procedure based on Genz’s numerical computation of probabilities from a multivariate normal distribution. This method is applied to the results of two-sample log-rank and weighted log-rank statistics where the survival data contained right-censored observations. We conducted Monte Carlo simulation studies not only to evaluate the familywise error rate and power of the proposed procedure but also to compare the procedure with conventional methods. The proposed method is also applied to the data set consisting of 8

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25

Pons, Odile. "Semi-parametric estimation for a semi-Markov process with left-truncated and right-censored observations." Statistics & Probability Letters 76, no. 9 (2006): 952–58. http://dx.doi.org/10.1016/j.spl.2005.10.030.

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26

Vanegas, Luis Hernando, and Gilberto A. Paula. "Log-symmetric regression models under the presence of non-informative left- or right-censored observations." TEST 26, no. 2 (2016): 405–28. http://dx.doi.org/10.1007/s11749-016-0517-z.

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27

Cole, Stephen R., Jessie K. Edwards, Ashley I. Naimi, and Alvaro Muñoz. "Hidden Imputations and the Kaplan-Meier Estimator." American Journal of Epidemiology 189, no. 11 (2020): 1408–11. http://dx.doi.org/10.1093/aje/kwaa086.

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Abstract The Kaplan-Meier (KM) estimator of the survival function imputes event times for right-censored and left-truncated observations, but these imputations are hidden and therefore sometimes unrecognized by applied health scientists. Using a simple example data set and the redistribution algorithm, we illustrate how imputations are made by the KM estimator. We also discuss the assumptions necessary for valid analyses of survival data. Illustrating imputations hidden by the KM estimator helps to clarify these assumptions and therefore may reduce inappropriate inferences.

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28

Andersen, Per Kragh, and Birgitte B. Ronn. "A Nonparametric Test for Comparing Two Samples Where All Observations are Either Left- or Right-Censored." Biometrics 51, no. 1 (1995): 323. http://dx.doi.org/10.2307/2533338.

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29

Nur Niswah Naslina, Azid Maarof, Arasan Jayanthi, Zulkafli Hani Syahida, and Adam Mohd Bakri. "Assessing the Goodness of Fit of the Gompertz Model in the Presence of Right and Interval Censored Data with Covariate." Austrian Journal of Statistics 49, no. 3 (2020): 57–71. http://dx.doi.org/10.17713/ajs.v49i3.1085.

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This research focuses on assessing the goodness of fit for the Gompertz model in the presence of right and interval censored data with covariate. The performance of the maximum likelihood estimates was evaluated via a simulation study at various censoring proportions and sample sizes. The conclusions were drawn based on the results of bias, standard error and root mean square error at different settings. Following that, another simulation study was carried out to compare the performance of the proposed modifications to the Cox-Snell residuals for both censored and uncensored observations at di

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30

Zhou, Jie, Jiajia Zhang, Alexander C. McLain, Wenbin Lu, Xuemei Sui, and James W. Hardin. "Semiparametric regression of the illness-death model with interval censored disease incidence time: An application to the ACLS data." Statistical Methods in Medical Research 29, no. 12 (2020): 3707–20. http://dx.doi.org/10.1177/0962280220939123.

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To investigate the effect of fitness on cardiovascular disease and all-cause mortality using the Aerobics Center Longitudinal Study, we develop a semiparametric illness-death model account for intermittent observations of the cardiovascular disease incidence time and the right censored data of all-cause mortality. The main challenge in estimation is to handle the intermittent observations (interval censoring) of cardiovascular disease incidence time and we develop a semiparametric estimation method based on the expectation-maximization algorithm for a Markov illness-death regression model. The

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31

Fernández, Arturo J. "Tolerance Limits and Sample-Size Determination Using Weibull Trimmed Data." Axioms 12, no. 4 (2023): 351. http://dx.doi.org/10.3390/axioms12040351.

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Guaranteed-coverage and expected-coverage tolerance limits for Weibull models are derived when, owing to restrictions on data collection, experimental difficulties, the presence of outliers, or some other extraordinary reasons, certain proportions of the extreme sample values have been censored or disregarded. Unconditional and conditional tolerance bounds are presented and compared when some of the smallest observations have been discarded. In addition, the related problem of determining minimum sample sizes for setting Weibull tolerance limits from trimmed data is discussed when the numbers

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32

Le Gat, Yves, Ingo Kropp, and Matthew Poulton. "Is the service life of water distribution pipelines linked to their failure rate?" Water Supply 13, no. 2 (2013): 386–93. http://dx.doi.org/10.2166/ws.2013.089.

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This paper aims to enable the relevant use of water main service lifetime and failure data to build a medium or long term infrastructure management plan. Firstly, how to estimate the service lifetime distribution of water mains using observations of decommissioning times which are possibly left-truncated and predominantly right-censored, is shown. Three methods are presented: a non-parametric method another based on the parametric Weibull distribution, and a third based on the parametric Herz distribution. An application with actual data related to grey cast iron water mains of two large Frenc

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33

Leemis, Lawrence M. "Computing the nonparametric estimator of the survivor function when all observations are either left- or right-censored with tied observation times." Computers & Operations Research 29, no. 5 (2002): 423–31. http://dx.doi.org/10.1016/s0305-0548(00)00077-0.

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34

Péron, Julien, Marc Buyse, Brice Ozenne, Laurent Roche, and Pascal Roy. "An extension of generalized pairwise comparisons for prioritized outcomes in the presence of censoring." Statistical Methods in Medical Research 27, no. 4 (2016): 1230–39. http://dx.doi.org/10.1177/0962280216658320.

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Generalized pairwise comparisons have been proposed to permit a comprehensive assessment of several prioritized outcomes between two groups of observations. This procedure estimates Δ, the net chance of a better outcome with treatment than with control by comparing the patients outcomes among all possible pairs taking one patient from the treatment group and one patient from the control group. For time to event outcomes, the standard procedure of generalized pairwise comparisons is analogous to the Gehan’s modification of the Mann-Whitney test which is biased in presence of censored observatio

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35

Sun, Liuquan, Shuwei Li, Lianming Wang, and Xinyuan Song. "A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup." Statistical Methods in Medical Research 30, no. 8 (2021): 1890–903. http://dx.doi.org/10.1177/09622802211023985.

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Failure time data with a cured subgroup are frequently confronted in various scientific fields and many methods have been proposed for their analysis under right or interval censoring. However, a cure model approach does not seem to exist in the analysis of partly interval-censored data, which consist of both exactly observed and interval-censored observations on the failure time of interest. In this article, we propose a two-component mixture cure model approach for analyzing such type of data. We employ a logistic model to describe the cured probability and a proportional hazards model to mo

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36

Jeon, Young Eun, Yongku Kim, and Jung-In Seo. "Predictive analysis of doubly Type-Ⅱ censored models." AIMS Mathematics 9, no. 10 (2024): 28508–25. http://dx.doi.org/10.3934/math.20241383.

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<p>The application of a doubly Type-Ⅱ censoring scheme, where observations are censored at both the left and right ends, is often used in various fields including social science, psychology, and economics. However, the observed sample size under this censoring scheme may not be large enough to apply a likelihood-based approach due to the occurrence of censoring at both ends. To effectively respond to this difficulty, we propose a pivotal-based approach within a doubly Type-Ⅱ censoring framework, focusing on two key aspects: Estimation for parameters of interest and prediction for missing

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37

Abdushukurov, A. A., and S. B. Bozorov. "Comparison of nonparametric estimates of the survival functions." Vestnik of Samara University. Natural Science Series 29, no. 3 (2023): 72–78. http://dx.doi.org/10.18287/2541-7525-2023-29-3-72-78.

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The article compares three types of estimates: exponential, multiplying and power structures for the survival function of three random censoring observations on the right. It was previously established that all these three estimates are equivalent with a growing sample size, i.e. three with the same centering and normalization converge to the same Gaussian process. For specific samples, it is shown that power estimates are defined on the entire line, in contrast to exponential and multiply estimates. Therefore, power estimates are better than the other two. Censored data is used in survival an

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38

Carlevaro, Fabrizio, and Yves Croissant. "On the use of the Box-Cox transformation in censored and truncated regression models." Model Assisted Statistics and Applications 15, no. 3 (2020): 197–214. http://dx.doi.org/10.3233/mas-200488.

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In this paper we revisit some issues related to the use of the Box-Cox transformation in censored and truncated regression models, which have been overlooked by the econometric and statistical literature. We first analyze the shape of the density function of the random variable which, rescaled by a Box-Cox transformation, leads to a normal random variable. Then, we identify the value ranges of the Box-Cox scale parameter for which a regular expectation of the derived random variable does not exist. This result calls for an extension of the concept of expectation, which can be computed regardle

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39

Jilani, Sd, S. Bhanu Prakash, A. Vasudeva Rao, K. Vijaya Bhaskara Reddy, and M. Sai. "Reliability Estimation of Scale Parameter in Type II Generalized Half-Logistic Distribution from Doubly Censored Samples Based on Monte Carlo Simulation." Indian Journal Of Science And Technology 17, no. 37 (2024): 3846–50. http://dx.doi.org/10.17485/ijst/v17i37.1911.

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Objectives: This article deals with estimation of the reliability function for one-parameter Type II Generalized Half- Logistic distribution (Type II GHLD). Methods: The Maximum likelihood (ML) and Approximate Maximum likelihood (AML) methods provided by Jilani et.al. 1 . Findings: Comparisons between the estimators were made using Monte Carlo Simulation based on statistical indicter bias and mean squared error (MSE). We have generated 3000 random samples of size n=10(5)20 from a standard one-parameter Type II GHLD with = 0.5, 1.5 and 2.0. Each sample is then ordered and from this sample a dou

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40

Bhattacharjee, Atanu, and Rajashree Dey. "Bayesian modelling for semi-competing risks data in the presence of censoring." Statistics in Transition new series 24, no. 3 (2023): 201–11. http://dx.doi.org/10.59170/stattrans-2023-044.

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In biomedical research, challenges to working with multiple events are often observed while dealing with time-to-event data. Studies on prolonged survival duration are prone to having numerous possibilities. In studies on prolonged survival, patients might die of other causes. Sometimes in the survival studies, patients experienced some events (e.g. cancer relapse) before dying within the study period. In this context, the semi-competing risks framework was found useful. Similarly, the prolonged duration of follow-up studies is also affected by censored observation, especially interval censori

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41

Jacqmin-Gadda, Hélène, Paul Blanche, Emilie Chary, Célia Touraine, and Jean-François Dartigues. "Receiver operating characteristic curve estimation for time to event with semicompeting risks and interval censoring." Statistical Methods in Medical Research 25, no. 6 (2016): 2750–66. http://dx.doi.org/10.1177/0962280214531691.

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Semicompeting risks and interval censoring are frequent in medical studies, for instance when a disease may be diagnosed only at times of visit and disease onset is in competition with death. To evaluate the ability of markers to predict disease onset in this context, estimators of discrimination measures must account for these two issues. In recent years, methods for estimating the time-dependent receiver operating characteristic curve and the associated area under the ROC curve have been extended to account for right censored data and competing risks. In this paper, we show how an approximat

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42

Ranjan, Rakesh, Rijji Sen, and Satyanshu K. Upadhyay. "Bayes analysis of some important lifetime models using MCMC based approaches when the observations are left truncated and right censored." Reliability Engineering & System Safety 214 (October 2021): 107747. http://dx.doi.org/10.1016/j.ress.2021.107747.

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43

Addison, John T., and Pedro Portugal. "The Effect of Advance Notification of Plant Closings on Unemployment." ILR Review 41, no. 1 (1987): 3–16. http://dx.doi.org/10.1177/001979398704100101.

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Using data from the 1984 Displaced Worker Survey, the authors model the determinants of time without work following job displacement for a large sample of workers laid off because of plant shutdowns between 1979 and 1984. The major focus of the paper is on the role of advance notification in mitigating unemployment. The estimating procedure accommodates right censored observations stemming from continuing or open-ended spells of unemployment. Advance notification is found to have significantly reduced the duration of unemployment of those notified workers who did not draw unemployment insuranc

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44

Powar, S. K. "Confidence interval estimation for reliability of a two parameter Weibull distribution under complete and censored samples." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 11 (2024): 1–7. http://dx.doi.org/10.55041/ijsrem38411.

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Estimating the reliability function of the two parameter Weibull distribution is a critical task in various fields, providing essential insights into product longevity and optimizing maintenance strategies. Due to its adaptable parameters namely scale parameter α and shape parameter β, the Weibull distribution models diverse failure behaviours, from early-life defects to wear-out periods. By evaluating reliability at key time phases namely early life (t < 0.1α), useful life (0.1α ≤ t ≤ α), and end-of-life (t > α), this estimation process supports quality control, operational forecasting,

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45

Boumaraf, Badreddine, Nacira Seddik-Ameur, and Vlad Stefan Barbu. "Estimation of Beta-Pareto Distribution Based on Several Optimization Methods." Mathematics 8, no. 7 (2020): 1055. http://dx.doi.org/10.3390/math8071055.

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This paper is concerned with the maximum likelihood estimators of the Beta-Pareto distribution introduced in Akinsete et al. (2008), which comes from the mixing of two probability distributions, Beta and Pareto. Since these estimators cannot be obtained explicitly, we use nonlinear optimization methods that numerically provide these estimators. The methods we investigate are the method of Newton-Raphson, the gradient method and the conjugate gradient method. Note that for the conjugate gradient method we use the model of Fletcher-Reeves. The corresponding algorithms are developed and the perfo

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Meribout, K. K., N. Seddik-Ameur, and H. Goual. "GOODNESS-OF-FIT TESTS FOR THE NEW WEIBULL-G FAMILY OF DISTRIBUTIONS." Advances in Mathematics: Scientific Journal 12, no. 1 (2023): 225–78. http://dx.doi.org/10.37418/amsj.12.1.15.

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In this paper, we present two New models named New-Weibull-Weibull ($NWW$) and New-Weibull-Rayleigh ($NWR$) from The New-Wei- bull-G family recently introduced that can have a variety of hazard rate shapes that allows to describe observations from different fields of study. The unknown parameters of the $NWW$ and $NWR$ models have been estimated under the maximum likelihood estimation method. Moreover, we construct a modified chi-squared goodness-of-fit test based on the \textit{Nikulin– Rao–Robson} ($NRR$) statistic to verify the applicability of the proposed $NWW$ and $NWR$ models. The modif

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Chambers, R. Christopher, and William C. Leggett. "Event Analysis Applied to Timing in Marine Fish Ontogeny." Canadian Journal of Fisheries and Aquatic Sciences 46, no. 9 (1989): 1633–41. http://dx.doi.org/10.1139/f89-208.

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We illustrate the utility of event analysis for characterizing timing in marine fish life histories, comparing event series among experimental groups, and predicting event timing in untested environments. Two examples using early life history traits are given, in example (1) we analyzed parental influence on metamorphosis timing in experimental laboratory populations of winter flounder (Pseudopleuronectes americanus). We fit a Weibull distribution to right-censored observations of age at metamorphosis and then estimated the fraction of individuals from each of two families that had become juve

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Khalid, Maryam, and Muhammad Aslam. "Bayesian Analysis of 3-Component Unit Lindley Mixture Model with Application to Extreme Observations." Mathematical Problems in Engineering 2022 (February 27, 2022): 1–22. http://dx.doi.org/10.1155/2022/1713375.

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Bayesian inference of the 3-component unit Lindley right censored mixture is presented in this paper. The posterior distributions of the parameters are derived assuming informative (gamma) as well as noninformative (uniform and Jeffreys) priors. For the gamma (informative) prior, hyperparameters are elicited using prior predictive distribution. The Bayesian estimation has been carried out considering both symmetric and asymmetric loss functions (squared error, quadratic, weighted, and precautionary loss functions). Simulation studies for various sample sizes and different threshold values (tes

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Sd., Jilani, Bhanu Prakash S, Vasudeva Rao A, Vijaya Bhaskara Reddy K, and Sai M. "Reliability Estimation of Scale Parameter in Type II Generalized Half-Logistic Distribution from Doubly Censored Samples Based on Monte Carlo Simulation." Indian Journal of Science and Technology 17, no. 37 (2024): 3846–50. https://doi.org/10.17485/IJST/v17i37.1911.

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Abstract <strong>Objectives:</strong> This article deals with estimation of the reliability function for one-parameter Type II Generalized Half- Logistic distribution (Type II GHLD). <strong>Methods:</strong> The Maximum likelihood (ML) and Approximate Maximum likelihood (AML) methods provided by Jilani et.al. 1 . <strong>Findings:</strong> Comparisons between the estimators were made using Monte Carlo Simulation based on statistical indicter bias and mean squared error (MSE). We have generated 3000 random samples of size n=10(5)20 from a standard one-parameter Type II

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Bumbulis, Laura S., and Richard J. Cook. "Robustness and Efficiency Considerations When Testing Process Reliability with a Limit of Detection." Mathematics 13, no. 8 (2025): 1274. https://doi.org/10.3390/math13081274.

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Processes in biotechnology are considered reliable if they produce samples satisfying regulatory benchmarks. For example, laboratories may be required to show that levels of an undesirable analyte rarely (e.g., in less than 5% of samples) exceed a tolerance threshold. This can be challenging when measurement systems feature a lower limit of detection, rendering some observations left-censored. We investigate the implications of detection limits on location-scale model-based inference in reliability studies, including their impact on large and finite sample properties of various estimators and

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