Accurate estimation of the volume and above-ground biomass exploitable trees by practice selective logging is essential for elaboration a sustainable management plan. The objective this study to develop machine learning models capable estimating commercial in Southwestern Amazon, based on dendrometric, climatic topographic characteristics. was carried out municipality Porto Acre, Acre state, Br...

GLM – General Linear Model Figure 2. Representative results from five patients. All panels: Top to bottom: mediolateral, coronal, craniocaudal sections; left:MR, right: DOT – beta values for the tumor model function. (a) 53 y, 33-mm IDC (model #1); (b) 77 y, 19-mm metaplastic CA (model #2); (c) 27 y, 22-mm fibroadenoma; (d) 37 y, 22-mm IDC; (e) 68 y, 16-mm IDC. 3 / 6 10 / 14 Sum 1 / 1 Melanoma ...

It is well known that using individual covariate information (such as body weight or gender) to model heterogeneity in capture–recapture (CR) experiments can greatly enhance inferences on the size of a closed population. Since individual covariates are only observable for captured individuals, complex conditional likelihood methods are usually required and these do not constitute a standard gen...

This article proposes a Bayesian spatio-temporal model for source reconstruction of M/EEG data. The usual two-level probabilistic model implicit in most distributed source solutions is extended by adding a third level which describes the temporal evolution of neuronal current sources using time-domain General Linear Models (GLMs). These comprise a set of temporal basis functions which are used ...

Owing to the sporadic nature of demand for aircraft maintenance repair parts, airline operators perceive dif%culties in forecasting and are still looking for superior forecasting methods. This paper deals with techniques applicable to predicting spare parts demand for airline 4eets. The experimental results of 13 forecasting methods, including those used by aviation companies, are examined and ...

Parametric statistical methods are traditionally employed in functional magnetic resonance imaging (fMRI) for identifying areas in the brain that are active with a certain degree of statistical significance. These parametric methods, however, have two major drawbacks. First, it is assumed that the observed data are Gaussian distributed and independent; assumptions that generally are not valid f...

Accurate estimates of development effort play an important role in the successful management of larger Web development projects. By applying measurement principles to measure qualities of the applications and their development processes, feedback can be obtained to help understand, control and improve products and processes. The objective of this paper is to present a Web design and authoring p...

This paper assesses and compares the performance of generalized linear models (GLM) with respect to log transformation and ANOVA approaches on the basis of coverage results and expected length of confidence intervals (CI) for the expected responses for exponentially distributed response variable. We also focus on the power functions of tests of hypothesis for testing significance of underlying ...

The general linear model (GLM) approach has arguably become the dominant way to analyze functional magnetic resonance imaging (fMRI) data. It tests whether activity in a brain region is systematically related to some known input function. However, the GLM becomes impractical when the precise timing and duration of psychological events cannot be specified a priori. In this work, we introduce a n...

The aim of this study was to evaluate the differences between cold carcass weights (CCW) for the Catalan Pyrenean horse (Cavall pirinenc català) breed according to different variables: area of origin, farm, gender and age. Linear regression models were applied using a generalized linear model (GLM) procedure for CCW of 397 animals (217 males and 180 females) slaughtered in a commercial abattoir...