This paper treats estimation in a class of new nonlinear threshold autoregressive models with both a stationary and a unit root regime. Existing literature on nonstationary threshold models have basically focused on models where the nonstationarity can be removed by differencing and/or where the threshold variable is stationary. This is not the case for the process we consider, and nonstandard ...

This paper proposes a class of new nonlinear threshold autoregressive models with both stationary and nonstationary regimes. Existing literature basically focuses on testing for a unit–root structure in a threshold autoregressive model. Under the null hypothesis, the model reduces to a simple random walk. Parameter estimation then becomes standard under the null hypothesis. How to estimate para...

We develop a general measure of estimation accuracy for fundamental research designs called v. The v measure compares the estimation accuracy of the ubiquitous Ordinary Least Squares estimator, which includes sample means as a special case, to a benchmark estimator which randomizes the direction of treatment effects. For sample and effect sizes common to experimental psychology, v suggests that...

The usual assumption behind robust design is that the number of replicates at each design point during an experimental stage is equal. In practice, however, it is often the case that this assumption is not met due to physical limitations and/or cost constraints. In this situation, using the usual method of ordinary least squares (OLS) to obtain fitted response functions for the mean and varianc...

Given a non-cooperative, continuous game, we describe a framework for parametric utility learning. Using heteroskedasticity inference, we adapt a Constrained Feasible Generalized Least Squares (cFGLS) utility learning method in which estimator variance is reduced, unbiased, and consistent. We extend our utility learning method using bootstrapping and bagging. We show the performance of the prop...

This study aimed to fit nonlinear regression models model the growth of characters fruit length (FL) and width (FW) pepper genotypes (Capsicum annuum L.) over time using method ordinary least squares (OLS); identify with best compare it obtained via quantile (QR) in 0.25, 0.5, 0.75 quantiles. Three (Logistic, Gompertz, von Bertalanffy) four quality evaluators were adopted: Akaike information cr...

In this paper we investigate the accuracy of cost estimates when applying most commonly used modeling techniques to a large-scale industrial data set which is professionally maintained by the International Software Standards Benchmarking Group (ISBSG). The modeling techniques applied are ordinary least squares regression (OLS), Analogy-based estimation, stepwise ANOVA, CART, and robust regressi...