Tree-ring samples from Chinese Pine (Pinus tabulaeformis Carr.) collected at Mt. Shimen on the western Loess Plateau, China, were used to reconstruct the mean May-July temperature during AD 1630-2011. The regression model explained 48% of the adjusted variance in the instrumentally observed mean May-July temperature. The reconstruction revealed significant temperature variations at interannual ...

Tree-ring data can extend back in time for thousands of years allowing researchers to reconstruct certain environmental factors that have left an imprint or signal in the tree-ring record. Typically, these factors include reconstructions of annual precipitation or temperature for months or seasons to which a particular tree species is sensitive. Over the last several decades, scientists have us...

Description of prediction guide The women’s most recent minimum data set (MDS) (collected on all nursing home residents in the US) was the primary source of information for the algorithm (total 75 variables). The data pertained to physical functioning and activities of daily living, ambulatory status, vision status, mood and behaviour patterns, incontinence, dementia, other health conditions, a...

We present a method for estimating monthly burned area globally at 1 spatial resolution using Terra MODIS data and ancillary vegetation cover information. Using regression trees constructed for 14 different global regions, MODIS active fire observations were calibrated to burned area estimates derived from 500-m MODIS imagery based on the assumption that burned area is proportional to counts of...

11 12 The objective of this study was to assess the utility of hyperspectral data in 13 estimating and mapping forest structural parameters including mean diameter-at14 breast-height (DBH), mean tree height and tree density of a closed canopy beech 15 forest (Fagus sylvatica L). Airborne HyMap images and data on forest structural 16 attributes were collected from the Majella National Park, Ital...

Estimating the parameters for a constant amplitude, polynomial-phase signal with additive Gaussian noise is considered. The difficulty in this problem is that there are many unobserved integers when a linear regression model is used for wrapped phases [I]. Analysing the least squares target function based on the regression model, we use the differencing approach [3] to simplify it. Thus a tree-...

Temporally frequent, cost-efficient and precise forest information requirements for national forest inventories, monitoring or protection tasks have grown over time and will continue to do so in the future. New perspectives are given by the airborne digital sensor ADS40, which provides entire image strips with high geometric, radiometric and temporal resolution (every three years for entire Swi...

Regression analysis is a machine learning approach that aims to accurately predict the value of continuous output variables from certain independent input variables, via automatic estimation of their latent relationship from data. Tree-based regression models are popular in literature due to their flexibility to model higher order non-linearity and great interpretability. Conventionally, regres...

Although regression trees were originally designed for large datasets, they can profitably be used on small datasets as well, including those from replicated or unreplicated complete factorial experiments. We show that in the latter situations, regression tree models can provide simpler and more intuitive interpretations of interaction effects as differences between conditional main effects. We...

This paper introduces a tree-based model that combines aspects of CART (Classification and Regression Trees) and STR (Smooth Transition Regression). The model is called the Smooth Transition Regression Tree (STR-Tree). The main idea relies on specifying a parametric nonlinear model through a tree-growing procedure. The resulting model can be analyzed as a smooth transition regression with multi...