All textbooks and articles dealing with classical tests in the context of linear models stress the implications of a significantly large F-ratio since it indicates that the mean square for whatever effect is being evaluated contains significantly more than just error variation. In general,...

Abstract Ridge regularized linear models (RRLMs), such as ridge regression and the SVM, are a popular group of methods that are used in conjunction with coefficient hypothesis testing to discover explanatory variables with a significant multivariate association to a response. However, many...

This paper uses a rich Norwegian dataset to re-examine the causal relationship between family income and child outcomes. Motivated by theoretical predictions and OLS results that suggest a nonlinear relationship, we depart from previous studies in allowing the marginal effects on children's...

Time series forecasting is an important area of forecasting in which past observations of the same variable are collected and analyzed to develop a model describing the underlying relationship. The model is then used to extrapolate the time series into the future. This modeling approach is...

The bootstrap is a computationally intensive data analysis technique. It is particularly useful for analysing small datasets, and for estimating the sampling distribution of a statistic when it is intractable. We focus on bootstrap hypothesis testing of linear models. In this context, at...

This research contrasts three econometric alternatives for stochastic efficiency frontier analysis: order – inter-quantile – and inverse order regression under the assumption of truncated error term distribution, and replicated moment estimation. The demonstration departs from a simple...

Citrus canker assessment data were used to investigate effects of using the Horsfall-Barratt (H-B) scale to estimate disease compared to direct estimation to the nearest percent. Twenty-eight raters assessed each of two-hundred infected leaves (0-38% true diseased area). The data were converted...