A class of random fields with two-piece marginal distributions for modeling point-referenced data with spatial outliers

In this paper, we propose a new class of non-Gaussian random fields named two-piece random fields. The proposed class allows to generate random fields that have flexible marginal distributions, possibly skewed and/or heavy-tailed and, as a consequence, has a wide range of applications. We study the second-order properties of this class and provide analytical expressions for the bivariate distribution and the associated correlation functions. We exemplify our general construction by studying two examples: two-piece Gaussian and two-piece Tukey-h random fields. An interesting feature of the proposed class is that it offers a specific type of dependence that can be useful when modeling data displaying spatial outliers, a property that has been somewhat ignored from modeling viewpoint in the literature for spatial point referenced data. Since the likelihood function involves analytically intractable integrals, we adopt the weighted pairwise likelihood as a method of estimation. The effectiveness of our methodology is illustrated with simulation experiments as well as with the analysis of a georeferenced dataset of mean temperatures in Middle East

ROCnReg: An R Package for Receiver Operating Characteristic Curve Inference With and Without Covariates

This paper introduces the package ROCnReg that allows estimating the pooled ROC curve, the covariate-specific ROC curve, and the covariate-adjusted ROC curve by different methods, both from (semi) parametric and nonparametric perspectives and within Bayesian and frequentist paradigms. From the estimated ROC curve (pooled, covariate-specific, or covariate-adjusted), several summary measures of discriminatory accuracy, such as the (partial) area under the ROC curve and the Youden index, can be obtained. The package also provides functions to obtain ROC-based optimal threshold values using several criteria, namely, the Youden index criterion and the criterion that sets a target value for the false positive fraction. For the Bayesian methods, we provide tools for assessing model fit via posterior predictive checks, while the model choice can be carried out via several information criteria. Numerical and graphical outputs are provided for all methods. This is the only package implementing Bayesian procedures for ROC curves

Quantifying uncertainties on excursion sets under a Gaussian random field prior

We focus on the problem of estimating and quantifying uncertainties on the excursion set of a function under a limited evaluation budget. We adopt a Bayesian approach where the objective function is assumed to be a realization of a Gaussian random field. In this setting, the posterior distribution on the objective function gives rise to a posterior distribution on excursion sets. Several approaches exist to summarize the distribution of such sets based on random closed set theory. While the recently proposed Vorob'ev approach exploits analytical formulae, further notions of variability require Monte Carlo estimators relying on Gaussian random field conditional simulations. In the present work we propose a method to choose Monte Carlo simulation points and obtain quasi-realizations of the conditional field at fine designs through affine predictors. The points are chosen optimally in the sense that they minimize the posterior expected distance in measure between the excursion set and its reconstruction. The proposed method reduces the computational costs due to Monte Carlo simulations and enables the computation of quasi-realizations on fine designs in large dimensions. We apply this reconstruction approach to obtain realizations of an excursion set on a fine grid which allow us to give a new measure of uncertainty based on the distance transform of the excursion set. Finally we present a safety engineering test case where the simulation method is employed to compute a Monte Carlo estimate of a contour line

mvord: An R Package for Fitting Multivariate Ordinal Regression Models

The R package mvord implements composite likelihood estimation in the class of multivariate ordinal regression models with a multivariate probit and a multivariate logit link. A flexible modeling framework for multiple ordinal measurements on the same subject is set up, which takes into consideration the dependence among the multiple observations by employing different error structures. Heterogeneity in the error structure across the subjects can be accounted for by the package, which allows for covariate dependent error structures. In addition, different regression coefficients and threshold parameters for each response are supported. If a reduction of the parameter space is desired, constraints on the threshold as well as on the regression coefficients can be specified by the user. The proposed multivariate framework is illustrated by means of a credit risk application

A Portuguese Adaptation of the Teruel Orthorexia Scale and a Test of Its Utility with Brazilian Young Adults

The aims for this study were to perform a Portuguese language cross-cultural adaptation of the Teruel Orthorexia Scale (TOS) and to evaluate the scale's psychometric properties, including verifying the frequency of behaviors characteristic of orthorexia nervosa and healthy orthorexia, among a group of Brazilian gym users. First, we adapted the Spanish version of the TOS to the Brazilian Portuguese language following international protocols to guarantee idiomatic, semantic, conceptual, and cultural equivalence. Then participants completed both the new Portuguese version of the TOS and a socioeconomic questionnaire. Among our sample of 226 young Brazilian adults (63.7% men; M age = 28.8, SD = 5.1 years), we assessed the bi-factorial model of the TOS through factorial, convergent, and discriminant validity, reliability, and factorial invariance. We calculated the mean scores of the TOS factors and the frequency of behaviors of both orthorexia nervosa and healthy orthorexia. The new Portuguese version was well understood by participants, and the TOS bi-factorial model presented adequate psychometric properties and showed invariance in independent subsamples and in men and women. The mean scores were different between sexes only for orthorexia nervosa, with women obtaining higher values. The frequency of orthorexia nervosa behaviors was 5.3% and of healthy orthorexia was 41.2%. Based on these findings, the Brazilian Portuguese version of the TOS can be a useful tool for investigating orthorexia-like behaviors in future research.info:eu-repo/semantics/publishedVersio

Investigating method effects associated with the wording direction of items of the Social Physique Anxiety Scale

Purpose The use of psychometric instruments to measure latent concepts is common. The development of these instruments usually involves mechanisms to reduce response bias, such as the inclusion of reversed items. The aim of this study was to investigate method efects related to the wording direction of the Social Physique Anxiety Scale (SPAS) items, a onedimensional instrument that assesses individual’s level of anxiety when others observe their body. Methods In total, 152 Brazilian adults (65.8% female) answered 2 formats of the SPAS: the original with 12 items (7 regular and 5 reversed); and a new format with all items written in the same direction (i.e., regular). Both formats were flled out at diferent times and alternately. Diferential item functioning analysis (DIF) and confrmatory factor analysis were conducted. Results The original SPAS did not ft the data, but after allowing covariances between all reversed items, the ft improved. The wording efect was supported by the DIF, indicating a better ft to the data for the new format with all items worded in the same direction. Conclusion The wording of the SPAS items had efect on the psychometric properties of instrument. When the wording of the reversed items was modifed, the factor model ftted the data. Future studies should take these fndings into account and evaluate the SPAS with all items worded in the same direction in diferent contexts. Level of evidence Descriptive (cross-sectional) study, Level V.info:eu-repo/semantics/publishedVersio