H ALEY and KNOTT (1992) developed a simple regression method for mapping quantitative trait loci (QTLs) using F2 populations. MARTINEZ and CURNOW (1992) considered the same approach using backcross populations. Studies that compare the regression method with that of LANDER and BOSTEIN’S (1989) maximum likelihood find very little difference between the two methods. The simple regression method o...

The package icenReg provides classic survival regression models for interval-censored data. We present an update to the package that extends the parametric models into the Bayesian framework. Core additions include functionality to define the regression model with the standard regression syntax while providing a custom prior function. Several other utility functions are presented that allow for...

In this thesis a methodology to construct prediction intervals for a generic black-box point forecast model is presented. The prediction intervals are learned from the forecasts of the black-box model and the actual realizations of the forecasted variable by using quantile regression on the observed prediction error distribution, the distribution of which is not assumed. An independent meta-mod...

We consider interval-valued data that frequently appear with advanced technologies in current data collection processes. Interval-valued data refer to the data that are observed as ranges instead of single values. In the last decade, several approaches to the regression analysis of interval-valued data have been introduced, but little work has been done on relevant statistical inferences concer...

In regression analysis the relationship between one response and a set of explanatory variables is investigated. The (response and explanatory) variables are usually single-valued. However, in several real-life situations, the available information may be formalized in terms of intervals. An interval-valued datum can be described by the midpoint (its center) and the radius (its half width). Her...

The comparative sensitivity of ordinal multiple regression (OMR) and least squares regression (LSR) to criterion variable deviations from interval scaling was investigated by way of computer simulation. LSR on raw scores and ranks was compared to OMR on raw scores, ranks and dominances. Simulated data sets varied on predictor variable correlations, amount of prediction error, weight distinctive...

We consider linear regression models where both input data (the values of independent variables) and output data (the observations of the dependent variable) are interval-censored. We introduce a possibilistic generalization of the least squares estimator, so called OLS-set for the interval model. This set captures the impact of the loss of information on the OLS estimator caused by interval ce...

Big data is a new trend at present, forcing the significant impacts on information technologies. In big data applications, one of the most concerned issues is dealing with large-scale data sets that often require computation resources provided by public cloud services. How to analyze big data efficiently becomes a big challenge. In this paper, we collaborate interval regression with the smooth ...

background: determining the mortality rate of diseases in a community is one of the main components in health care planning of that community. this study used a join point regression model to determine the trend of mortality due to diabetes mellitus (dm) in iran. materials and methods: the data on the rate of mortality due to dm were obtained from the reports of the iranian ministry of health. ...