We analyze the utility of multiscale supervised classification algorithms for object detection and extraction from laser scanning or photogrammetric point clouds. Only the geometric information (the point ...
Instrumental variable (IV) methods are widely used for estimating average treatment effects in the presence of unmeasured confounders. However, the capability of existing IV procedures, and most notably ...
In this paper, we consider a general regression model where missing data occur in the response and in the covariates. Our aim is to estimate the marginal distribution function and a marginal functional, ...
Goodness–of–fit tests for quantile regression models, in the presence of missing observations in the response variable, are introduced and analyzed in this paper. The different proposals are based on the ...
Survival analysis includes a wide variety of methods for analyzing time‐to‐event data. One basic but important goal in survival analysis is the comparison of survival curves between groups. Several nonparametric ...
Survival to extreme ages clusters within families. However, identifying genetic loci conferring longevity and low morbidity in such longevous families is challenging. There is debate concerning the survival ...
Background The long-term effectiveness of atherectomy treatment for peripheral arterial disease is unknown. We studied 5-year clinical outcomes by endovascular treatment type among patients with peripheral ...
The use of the area under the receiver-operating characteristic, ROC, curve (AUC) as an index of diagnostic accuracy is overwhelming in fields such as biomedical science and machine learning. It seems ...
Two‐stage instrumental variable methods are commonly used for estimating average causal effects in the presence of an unmeasured confounder. In the context of the proportional hazard Cox regression models, ...
The CODEX index was developed and validated in patients hospitalized for COPD exacerbation to predict the risk of death and readmission within one year after discharge. Our study aimed to validate the ...
The Internet emerged as a powerful infrastructure for the worldwide communication and interaction of people. Some unethical uses of this technology (for instance spam or viruses) generated challenges in ...
In this research, an algorithm is presented for predicting the remaining useful life (RUL) of aircraft engines from a set of predictor variables measured by several sensors located in the engine. RUL prediction ...
The paper first introduces a new two-parameter continuous probability distribution
with bounded support from the extended exponential-geometric distribution. Closed-
form expressions are given for the ...
Auxiliary information x is commonly used in survey sampling at the estimation
stage. We propose an estimator of the finite population distribution function
Fy(t) when x is available for all units in ...
Assessment of the diagnostic accuracy of biomarkers through receiver operating characteristic curve analysis frequently involves a limit of detection imposed by the laboratory analytical system precision. ...
The aim of this study was to provide percentile curves and reference values for the performance in 2000-m maximal effort on rowing ergometer. A cross-sectional study was carried out with a non-probabilistic ...
Objective
Use logistic regression to determine a mathematical model which is able to predict injuries in aerobic gymnastics (AG) athletes, according to certain anthropometric characteristics.
Subjects ...
The receiver operating characteristic (ROC) curve is a graphical method which has become standard in the analysis of diagnostic markers, that is, in the study of the classification ability of a numerical ...
Enriching existing predictive models with new biomolecular markers is an important task in the new multi-omic era. Clinical studies increasingly include new sets of omic measurements which may prove their ...
... time, the asymptotic normality of the maximum EL and PEL estimators of the parameter is established. Also, the variable selection of the model in the presence and absence of auxiliary information, respectively, ...
In the field of aging research, family-based sampling study designs are commonly used to study the lifespans of long-lived family members. However, the specific sampling procedure should be carefully taken ...
... by using group-based variable selection or group-specific penalization. We compare the performance of our new approaches with standard regularized regression via simulations. Based on these results we ...
The receiver operating characteristic curve is a popular graphical method often used to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, ...
This paper presents a general result that allows for establishing a link between the Kolmogorov-Marcinkiewicz-Zygmund strong law of large numbers and Feller's strong law of large numbers in a Banach space ...
This paper studies the estimation of the characteristic function of a finite population. Specifically, the weak convergence of the finite population empirical characteristic process is studied. Under suitable ...
In this paper we analyse multi-agent inventory systems where each agent has a deterministic demand and a capacitated warehouse with constant holding costs. Additionally, shortages are not allowed, the ...
... the variable selection of the covariates in the linear part by adopting adaptive LASSO penalty. Under appropriate assumptions, the asymptotic normality of the proposed estimators is established, and the ...
Based on empirical likelihood method, we construct new weighted estimators of conditional density and conditional survival functions when the interest random variable is subject to random left-truncation; ...
... kernel smoothing for variable selection in functional data and a wavelet-based weighted LASSO functional linear regression. Our approach proved to have some advantages over these two testing approaches, ...
Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous ...
Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous ...
Instrumental variable (IV) methods are widely used for estimating average treatment effects in the presence of unmeasured confounders. However, the capability of existing IV procedures, and most notably ...
When developing prediction models for application in clinical practice, health practitioners usually categorise clinical variables that are continuous in nature. Although categorisation is not regarded ...
This paper addresses the problem of hypothesis test on response mean with various inequality constraints in the presence of covariates when response data are missing at random. The various hypotheses include ...
In Survival Analysis and related fields of research right-censored and left-truncated data often appear. Usually, it is assumed that the right-censoring variable is independent of the lifetime of ultimate ...
The Cox proportionalhazards model is the most widely used survival predictionmodel for analysing time-to-event data. To measure the discrimination ability of a survival model the concordance probability ...
Adjustment for spatial trends in plant breeding field trials is essential for efficient evaluation and selection of genotypes. Current mixed model methods of spatial analysis are based on a multi-step ...
Recent advances in information technologies are generating a growth in the amount of available biomedical data. In this paper, we studied the impact sample size may have on the categorisation of a continuous ...
We present the R npregfast package via some applications involved with the study of living organisms. The package implements nonparametric estimation procedures in regression models with or without factor-by-curve ...
This paper studies properties of parameter estimators obtained by minimizing a distance between the empirical probability generating function and the probability generating function of a model for count ...
In the field of aging research, family-based sampling study designs are commonly used to study the lifespans of long-lived family members. However, the specific sampling procedure should be carefully taken ...
In multiple regression models, when there are a large number (p) of explanatory variables which may or may not be relevant for predicting the response, it is useful to be able to reduce the model. To this ...
... estimation and variable selection of the model are investigated, the proposed PEL estimators are shown to possess the oracle property. Also, we introduce the PEL ratio statistic to test a linear hypothesis ...
The Log-Lindley distribution is a continuous probability model with useful applications in insurance and inventory management. In this note, it is proven that pseudo-random data from this model can be ...
Background: Debate regarding the prognosis of asymptomatic patients with Brugada syndrome (BrS) is possibly affected by the selection bias of survivors of sudden cardiac arrest (SCA). We aimed to determine ...
Receiver operating-characteristic (ROC) curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent ...
A test approach to the model selection problem based on characteristic functions (CFs) is proposed. The scheme is close to that proposed by Vuong (Econometrica 57:257–306, 1989), which is based on comparing ...
We evaluated specific habitat features (bottom substrate type, depth, temperature, season and latitude-longitude) at random locations in the Cíes Islands (Galician Atlantic Islands National Park, Northwest ...
This paper analyses the behaviour of the goodness-of-fit tests for regression models. To this end, it uses statistics based on an estimation of the integrated regression function with missing observations ...
Beta-binomial sequential goodness-of-fit (or BB-SGoF) method for multiple
testing has been recently proposed as a suitable modification of the sequential
goodness-of-fit (SGoF) multiple testingmethod ...