Search results for "Linear regression"
showing 10 items of 375 documents
On the ambiguous consequences of omitting variables
2015
This paper studies what happens when we move from a short regression to a long regression (or vice versa), when the long regression is shorter than the data-generation process. In the special case where the long regression equals the data-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias and mean squared error comparisons and study the dependence of the differences on the misspecification parameter.
Oxygen Consuming Regions in EMT60/Ro Multicellular Tumour Spheroids Determined by Nonlinear Regression Analysis of Experimental PO2 Profiles
1987
Malignant cells can be studied in vitro, in a tumour-like microenvironment, by growing multicellular tumour spheroids in culture (Sutherland, McCredie and Inch, 1971). Franko and Sutherland (1979) utilized diffusion theory to explain the viable rim thicknesses of spheroids measured histologically. Without PO2 profiles, however, an unequivocal interpretation of their results was not possible. Systematic studies of the PO2 profiles in spheroids have since been made with oxygen microelectrodes by several groups (Carlsson et al., 1979; Kaufman et al., 1981; Mueller-Klieser and Sutherland, 1982a,b). Based on these measurements, new analyses utilizing diffusion theory are being developed to chara…
Substituent effects on13C NMR parameters of chlorinated diphenyl ethers. A multiple linear regression analysis
1995
13C NMR chemical shifts and nJ(C,H) coupling constants of polychlorinated diphenyl ethers (PCDEs) were measured and analysed. The chlorine substituent effects on the chemical shifts and the coupling constants were determined by a multiple linear regression analysis. The 13C NMR chemical shifts depend on the conformational preferences in PCDEs. In addition to single substituent effects, corrective terms reflecting the conformational state of the molecule and the mutual steric interactions of two chlorine atoms had to be taken into account for the reliable prediction of the 13C chemical shifts. In contrast to chemical shifts, conformational effects play a minor role in the substituent effects…
Food consumer models: The case of the responsible consumer
2017
The profile of the responsible consumer, that is, an individual whose purchases strive to satisfy altruistic aims above and beyond oneâs merely personal consumer necessities, is closely correlated to the oneâs socio-economic conditions. All subjective aspects considered, the correlation between responsible consumption in the agri-food sector and the level of education of the individual was studied herein by way of a statistical survey, conducted on a sample of 108 individuals. Likewise, the correlation between the level of responsible consumption and the average monthly expenditures was also elucidated. The study was carried out using the statistical software environment R and the resul…
Disentangling cardiovascular control mechanisms during head-down tilt via joint transfer entropy and self-entropy decompositions
2015
A full decomposition of the predictive entropy (PE) of the spontaneous variations of the heart period (HP) given systolic arterial pressure (SAP) and respiration (R) is proposed. The PE of HP is decomposed into the joint transfer entropy (JTE) from SAP and R to HP and self-entropy (SE) of HP. The SE is the sum of three terms quantifying the synergistic/redundant contributions of HP and SAP, when taken individually and jointly, to SE and one term conditioned on HP and SAP denoted as the conditional SE (CSE) of HP given SAP and R. The JTE from SAP and R to HP is the sum of two terms attributable to SAP or R plus an extra term describing the redundant/synergistic contribution to the JTE. All q…
Análisis de métodos de validación cruzada para la obtención robusta de parámetros biofísicos
2015
[EN] Non-parametric regression methods are powerful statistical methods to retrieve biophysical parameters from remote sensing measurements. However, their performance can be affected by what has been presented during the training phase. To ensure robust retrievals, various cross-validation sub-sampling methods are often used, which allow to evaluate the model with subsets of the field dataset. Here, two types of cross-validation techniques were analyzed in the development of non-parametric regression models: hold-out and k-fold. Selected non-parametric linear regression methods were least squares Linear Regression (LR) and Partial Least Squares Regression (PLSR), and nonlinear methods were…
The influence of climate change on the soil organic carbon content in Italy from 1961 to 2008
2011
Abstract Soils are the biggest carbon store in the world (1500 Gt, e.g. 1.5 × 10 21 g). The European Commission indicates the accounting of soil organic carbon (SOC) variations in space and time as the first step in the strategy for soil protection. It is indeed necessary in evaluating the risk of soil organic matter decline and soil biodiversity decline, and when evaluating the role played by soils in global CO 2 accounting. Previous maps of SOC variations in Italy did not consider the direct effect of climate. There is a marked inter-dependence between SOC and climate. SOC increases with the increase in precipitations and decreases with a rise in temperatures. It is also known that land …
Comparative study of modelling the thermal efficiency of a novel straight through evacuated tube collector with MLR, SVR, BP and RBF methods
2021
Abstract Data-based methods are useful for accurate modelling of solar thermal systems. In this work, several artificial neural network (ANN) techniques are proposed to predict the thermal performance of an all-glass straight through evacuated tube solar collector. These are compared to support vector regression analysis. Extensive experimental data sets were collected for training the ANN models. Solar radiation intensity, ambient temperature, wind speed, mass flow rate and collector inlet temperature were selected as the input layer to predict the thermal efficiency of the solar collector. The prediction precision of the ANN models was compared to the multiple linear regression and suppor…
Using the Breeder genetic algorithm to optimize a multiple regression analysis model used in prediction of the mesiodistal width of unerupted teeth
2014
For the prediction of the unerupted canine and premolars mesiodistal size, have been proposed different variants of multiple linear regression equations (MLRE). These are based on the amount of the upper and lower permanent incisors with a tooth of the lateral support. Aim of present study was to develop a method for optimization of MLRE, using a genetic algorithm for determining a set of coefficients that minimizes the prediction error for the sum of permanent premolars and canines dimensions from a group of young people in an area Romania's central city represented by Sibiu. To test the proposed method, we used a multiple linear regression equation derived from the estimation method propo…
The Perception and Attitudes Towards City Garbage Management: A First Analysis
2017
The main aim of this paper is to to explore the perception and attitude of people toward an important issue like the City Garbage Management. A new Survey Questionnaire to measure the perception and attitudes towards city garbage management has been developed by the Authors, in order to realize a very first analysis of compatibility of the Comprehensive Action Determination Model - CADM (Klöckner, 2013) with City Garbage Management issues. To test the application of the CADM model to City Garbage Management, a simple linear regression was calculated to predict the dependent variables based on predictor variables according the CADM model. The linear regression analysis shows a first confirma…