A growing field is related to automatized Time Series analysis, through complicated due to the de... more A growing field is related to automatized Time Series analysis, through complicated due to the dependence of observed and hidden dimensions often presented in these data types. In this report the problem is motivated by a Brazilian financial company interested in unraveling relation structure explanation of the Japanese' CPI ex-fresh Food \& Energy across 157 economical exogenous variables, with very limiting data. The problem becomes more complex when considering that each variable can enter the model with lags of 0 to 8 periods, as well as an additional restriction of admitting only a positive relationship. This report discusses three possible treatments involving models for structured time series, the most relevant approach found in this study is a Dynamic Regression Model combined with a Stepwise algorithm, which allows the most relevant variables, as well as their respective lags, to be found and inserted in the model with low computational cost.
Cure fraction is not an easy task to be calculated relating probabilistic estimations to an event... more Cure fraction is not an easy task to be calculated relating probabilistic estimations to an event. For instance, cancer patients may abandon treatment, be cured, or die due to another illness, causing limitations regarding the information about the odds of cancer cure (related to the patient follow-up) and may mislead the researcher's inference. In this paper, we overcame this limitation and proposed a risk assessment tool related to the lifetime of cancer patients to survival functions to help medical decision-making. Moreover, we proposed a new machine learning algorithm, so-called long-term generalized weighted Lindley (LGWL) distribution, solving the inferential limitation caused by the censored information. Regarding the robustness of this distribution, some mathematical properties are shown and inferential procedures discussed, under the maximum likelihood estimators' perspective. Empirical results used TCGA lung cancer data (but not limited to this cancer type) showin...
In this paper we proposed a new lifetime distribution namely generalized weighted Lindley (GLW) d... more In this paper we proposed a new lifetime distribution namely generalized weighted Lindley (GLW) distribution. The GLW distribution is a straightforwardly generalization of the weighted Lindley distribution proposed by Ghitany et al. [A two-parameter weighted Lindley distribution and its applications to survival data, Mathematics and Computers in Simulation 81, (2011) p.1190-1201], which accommodates increasing, decreasing, decreasing-increasing-decreasing, bathtub, or unimodal hazard functions, making the GWL distribution a flexible model for reliability data. We provide a significant account of mathematical properties of the new distribution. Different estimation procedures are also presented such as, the maximum likelihood estimators, method of moments,the ordinary and weighted least-squares, percentile, maximum product of spacings and minimum distance estimators. The different estimators are compared by using extensive numerical simulations Finally, we analyze two data sets for i...
Abstract. In this paper, we introduce the random deterioration rate model with measurement error ... more Abstract. In this paper, we introduce the random deterioration rate model with measurement error in order to incorporate the variability among different components. The motivation behind the random variable model is to capture the randomness in the individual differences across the population. This model incorporates only sample uncertainty of the degradation, and no temporal variability is included. The measurement error models appear to overcome this problem. The random rate analysis is based on repeated measurements of failure sizes generated by a degradation process over time in a components population. Some characteristics of the random deterioration rate model based on the inverse Gaussian distribution and subject to measurement error, are examined. We carry out simulation studies to (i) assess the performance of the maximum likelihood estimates obtained through the Gaussian quadrature along with Quasi-Newton optimization method; and (ii) examine the effects of model misspecif...
This article focus on the analysis of the reliability of multiple identical systems that can have... more This article focus on the analysis of the reliability of multiple identical systems that can have multiple failures over time. A repairable system is defined as a system that can be restored to operating state in the event of a failure. This work under minimal repair, it is assumed that the failure has a power law intensity and the Bayesian approach is used to estimate the unknown parameters. The Bayesian estimators are obtained using two objective priors know as Jeffreys and reference priors. We proved that obtained reference prior is also a matching prior for both parameters, i.e., the credibility intervals have accurate frequentist coverage, while the Jeffreys prior returns unbiased estimates for the parameters. To illustrate the applicability of our Bayesian estimators, a new data set related to the failures of Brazilian sugar cane harvesters is considered.
In this paper, we propose a hierarchical statistical model for a single repairable system subject... more In this paper, we propose a hierarchical statistical model for a single repairable system subject to several failure modes (competing risks). The paper describes how complex engineered systems may be modelled hierarchically by use of Bayesian methods. It is also assumed that repairs are minimal and each failure mode has a power-law intensity. Our proposed model generalizes another one already presented in the literature and continues the study initiated by us in another published paper. Some properties of the new model are discussed. We conduct statistical inference under an objective Bayesian framework. A simulation study is carried out to investigate the efficiency of the proposed methods. Finally, our methodology is illustrated by two practical situations currently addressed in a project under development arising from a partnership between Petrobras and six research institutes.
The present work intends to study the effectiveness of applying Manchester Triage System to impro... more The present work intends to study the effectiveness of applying Manchester Triage System to improve patient flow in a Brazilian hospital, which allow a more welcoming and decisive service. Thus, time to event techniques are applied based on parametric regression models with the objective of investigating indicators for the emergency/urgency sector and thus, contributing to better operational efficiency. The results show that different explanatory variables such as classification, age, period, among others, influence in the time of attendance. At the end, we provide a simple model that can be used to predict such time under different explanatory variable for a particular Brazilian hospital.
A new one-parameter distribution is proposed in this paper. The new distribution allows for the o... more A new one-parameter distribution is proposed in this paper. The new distribution allows for the occurrence of instantaneous failures (inliers) that are natural in many areas. Closed-form expressions are obtained for the moments, mean, variance, a coefficient of variation, skewness, kurtosis, and mean residual life. The relationship between the new distribution with the exponential and Lindley distributions is presented. The new distribution can be viewed as a combination of a reparametrized version of the Zakerzadeh and Dolati distribution with a particular case of the gamma model and the occurrence of zero value. The parameter estimation is discussed under the method of moments and the maximum likelihood estimation. A simulation study is performed to verify the efficiency of both estimation methods by computing the bias, mean squared errors, and coverage probabilities. The superiority of the proposed distribution and some of its concurrent distributions are tested by analyzing four...
In this paper, we consider to evaluate the efficiency of volleyball players according to the perf... more In this paper, we consider to evaluate the efficiency of volleyball players according to the performance of attack, block and serve, but considering the compositional structure of the data related to the fundaments. The finite mixture of regression models better fitted the data in comparison with the usual regression model. The maximum likelihood estimates are obtained via an EM algorithm. A simulation study revels that the estimates are closer to the real values, the estimators are asymptotically unbiased for the parameters. A real Brazilian volleyball dataset related to the efficiency of the players is considered for the analysis.
A growing field is related to automatized Time Series analysis, through complicated due to the de... more A growing field is related to automatized Time Series analysis, through complicated due to the dependence of observed and hidden dimensions often presented in these data types. In this report the problem is motivated by a Brazilian financial company interested in unraveling relation structure explanation of the Japanese' CPI ex-fresh Food \& Energy across 157 economical exogenous variables, with very limiting data. The problem becomes more complex when considering that each variable can enter the model with lags of 0 to 8 periods, as well as an additional restriction of admitting only a positive relationship. This report discusses three possible treatments involving models for structured time series, the most relevant approach found in this study is a Dynamic Regression Model combined with a Stepwise algorithm, which allows the most relevant variables, as well as their respective lags, to be found and inserted in the model with low computational cost.
Cure fraction is not an easy task to be calculated relating probabilistic estimations to an event... more Cure fraction is not an easy task to be calculated relating probabilistic estimations to an event. For instance, cancer patients may abandon treatment, be cured, or die due to another illness, causing limitations regarding the information about the odds of cancer cure (related to the patient follow-up) and may mislead the researcher's inference. In this paper, we overcame this limitation and proposed a risk assessment tool related to the lifetime of cancer patients to survival functions to help medical decision-making. Moreover, we proposed a new machine learning algorithm, so-called long-term generalized weighted Lindley (LGWL) distribution, solving the inferential limitation caused by the censored information. Regarding the robustness of this distribution, some mathematical properties are shown and inferential procedures discussed, under the maximum likelihood estimators' perspective. Empirical results used TCGA lung cancer data (but not limited to this cancer type) showin...
In this paper we proposed a new lifetime distribution namely generalized weighted Lindley (GLW) d... more In this paper we proposed a new lifetime distribution namely generalized weighted Lindley (GLW) distribution. The GLW distribution is a straightforwardly generalization of the weighted Lindley distribution proposed by Ghitany et al. [A two-parameter weighted Lindley distribution and its applications to survival data, Mathematics and Computers in Simulation 81, (2011) p.1190-1201], which accommodates increasing, decreasing, decreasing-increasing-decreasing, bathtub, or unimodal hazard functions, making the GWL distribution a flexible model for reliability data. We provide a significant account of mathematical properties of the new distribution. Different estimation procedures are also presented such as, the maximum likelihood estimators, method of moments,the ordinary and weighted least-squares, percentile, maximum product of spacings and minimum distance estimators. The different estimators are compared by using extensive numerical simulations Finally, we analyze two data sets for i...
Abstract. In this paper, we introduce the random deterioration rate model with measurement error ... more Abstract. In this paper, we introduce the random deterioration rate model with measurement error in order to incorporate the variability among different components. The motivation behind the random variable model is to capture the randomness in the individual differences across the population. This model incorporates only sample uncertainty of the degradation, and no temporal variability is included. The measurement error models appear to overcome this problem. The random rate analysis is based on repeated measurements of failure sizes generated by a degradation process over time in a components population. Some characteristics of the random deterioration rate model based on the inverse Gaussian distribution and subject to measurement error, are examined. We carry out simulation studies to (i) assess the performance of the maximum likelihood estimates obtained through the Gaussian quadrature along with Quasi-Newton optimization method; and (ii) examine the effects of model misspecif...
This article focus on the analysis of the reliability of multiple identical systems that can have... more This article focus on the analysis of the reliability of multiple identical systems that can have multiple failures over time. A repairable system is defined as a system that can be restored to operating state in the event of a failure. This work under minimal repair, it is assumed that the failure has a power law intensity and the Bayesian approach is used to estimate the unknown parameters. The Bayesian estimators are obtained using two objective priors know as Jeffreys and reference priors. We proved that obtained reference prior is also a matching prior for both parameters, i.e., the credibility intervals have accurate frequentist coverage, while the Jeffreys prior returns unbiased estimates for the parameters. To illustrate the applicability of our Bayesian estimators, a new data set related to the failures of Brazilian sugar cane harvesters is considered.
In this paper, we propose a hierarchical statistical model for a single repairable system subject... more In this paper, we propose a hierarchical statistical model for a single repairable system subject to several failure modes (competing risks). The paper describes how complex engineered systems may be modelled hierarchically by use of Bayesian methods. It is also assumed that repairs are minimal and each failure mode has a power-law intensity. Our proposed model generalizes another one already presented in the literature and continues the study initiated by us in another published paper. Some properties of the new model are discussed. We conduct statistical inference under an objective Bayesian framework. A simulation study is carried out to investigate the efficiency of the proposed methods. Finally, our methodology is illustrated by two practical situations currently addressed in a project under development arising from a partnership between Petrobras and six research institutes.
The present work intends to study the effectiveness of applying Manchester Triage System to impro... more The present work intends to study the effectiveness of applying Manchester Triage System to improve patient flow in a Brazilian hospital, which allow a more welcoming and decisive service. Thus, time to event techniques are applied based on parametric regression models with the objective of investigating indicators for the emergency/urgency sector and thus, contributing to better operational efficiency. The results show that different explanatory variables such as classification, age, period, among others, influence in the time of attendance. At the end, we provide a simple model that can be used to predict such time under different explanatory variable for a particular Brazilian hospital.
A new one-parameter distribution is proposed in this paper. The new distribution allows for the o... more A new one-parameter distribution is proposed in this paper. The new distribution allows for the occurrence of instantaneous failures (inliers) that are natural in many areas. Closed-form expressions are obtained for the moments, mean, variance, a coefficient of variation, skewness, kurtosis, and mean residual life. The relationship between the new distribution with the exponential and Lindley distributions is presented. The new distribution can be viewed as a combination of a reparametrized version of the Zakerzadeh and Dolati distribution with a particular case of the gamma model and the occurrence of zero value. The parameter estimation is discussed under the method of moments and the maximum likelihood estimation. A simulation study is performed to verify the efficiency of both estimation methods by computing the bias, mean squared errors, and coverage probabilities. The superiority of the proposed distribution and some of its concurrent distributions are tested by analyzing four...
In this paper, we consider to evaluate the efficiency of volleyball players according to the perf... more In this paper, we consider to evaluate the efficiency of volleyball players according to the performance of attack, block and serve, but considering the compositional structure of the data related to the fundaments. The finite mixture of regression models better fitted the data in comparison with the usual regression model. The maximum likelihood estimates are obtained via an EM algorithm. A simulation study revels that the estimates are closer to the real values, the estimators are asymptotically unbiased for the parameters. A real Brazilian volleyball dataset related to the efficiency of the players is considered for the analysis.
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