NCSU, Princeton University, and UC-Davis Abstract: Functional linear regression analysis aims to model regression relations which include a functional predictor. The analogue to the regression parameter vector or matrix in conventional multivariate or multiple-response linear regression models is a regression parameter function in one or two arguments. If in addition one has scalar predictors, ...

We study the generation and visualization of residuals for detecting and identifying unseen faults using autoassociative models learned from process data. Least squares and kernel regression models are compared on the basis of their ability to describe the support of the data. Theoretical results show that kernel regression models are more appropriate in this sense. Moreover, experiments on vib...

growth analysis is a valuable method in the quantitative analysis of crop growth, development and crop production. there are many regression models to describe the sigmoid growth patterns. by considering that, the parameters of non-linear regression models have physiological meanings, they are preferable relation to linear regression models. the aim of this study was to collect and evaluate the...

Nonlinear regression analysis holds significant popularity in mathematical, engineering, and social science domains. Disciplines like financial matters, biology, natural chemistry have broadly utilized nonlinear models (NLRMs). Cloned datasets their own importance such areas which provide the same fit of bivariate multivariate for actual datasets. This article presents a sequence cloned that gi...

Causal learning methods are often evaluated in terms of their ability to discover a true underlying directed acyclic graph (DAG) structure. However, in general the true structure is unknown and may not be a DAG structure. We therefore consider evaluating causal learning methods in terms of predicting the effects of interventions on unseen test data. Given this task, we show that there exist a v...

Regression trees are tree-based models used to solve those prediction problems in which the response variable is numeric. They differ from the better-known classification or decision trees only in that they have a numeric value rather than a class label associated with the leaves. Model trees are an extension of regression trees in the sense that they associate leaves with multivariate linear m...

Active Appearance Models (AAMs) are widely used to fit shape models to new images. Recently it has been demonstrated that non-linear regression methods and sequences of AAMs can significantly improve performance over the original linear formulation. In this paper we focus on the ability of a model trained on one dataset to generalise to other sets with different conditions. In particular we com...

The two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae), is an economically important pest of ornamental plant in Iran. The population abundance and spatial distribution were studied on five Rosa cultivars including Maroussia, Wendela, Elderado, Wenedetta, and Hot Lady during two growing seasons of 2011 and 2012 in greenhouse. The k parameter, index of dispersion, Lloyd’s m...