Linear regression
Top PDF Linear regression:
Standardizing effect size from linear regression models with log-transformed variables for meta-analysis
... Background: Meta-analysis is very useful to summarize the effect of a treatment or a risk factor for a given disease. Often studies report results based on log-transformed variables in order to achieve the principal ...
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Literature review on linear regression equations for relating water activity to moisture content in floral honeys : development of a weighted average equation
... literature linear equations was made which takes into account the number of data points as well as the precision involved in the different literature ...average linear regression equation is a ...
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Area-Efficient Linear Regression Architecture for Real-Time Signal Processing on FPGAs
... In this work we have focused on a linear regression method that has been widely used in many signal processing applications, such as [5]–[7]. We have designed an FPGA-oriented architecture that efficiently ...
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Chapter 5 Linear Regression and Correlation Simple and Multiple 2020 ppt
... in regression analysis refers to how strongly interrelated the independent variables in a model ...Most regression programs can compute variance inflation factors (VIF) for each ...
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A research agenda on general to specific spatial model search
... classical linear regression model against a heteroskedastic spatially dependent alternative, and recently a practical algorithm for estimating Anselin’s model by maximizing the Normal likelihood has been ...
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Publicidad, pluralismo y elecciones: gobiernos locales y sus gastos en medios de comunicación
... multiple linear regression model, where the municipalities acted as units of analysis, defining municipal media spending during the 2016 election year as a dependent variable and different attributes of the ...
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Statistically coherent calibration of X Ray Fluorescence Spectrometry for major elements in rocks in minerals
... heteroscedastic linear regression system, even if each error or noise term is still Gaussian, the OLR model is no longer the maximum likelihood estimate and consequently, it is no longer efficient ...handle ...
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Association between allergic rhinitis and asthma control in Peruvian school children: a cross-sectional study.
... Copyright © 2013 Justo Padilla et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the ...
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Additive effects of LPL, APOA5 and APOE variant combinations on triglyceride levels and hypertriglyceridemia: results of the ICARIA genetic sub-study.
... multivariate linear regression model with dummy variables for categorical terms was elaborated to test the null hypothesis of no association between each genetic variant assessed and log-TG, adjusting for ...
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Modelación de la concentración atmosférica de CO usando regresión no paramétrica con bandas de variabilidad no homogéneas
... we found the lowest dispersion. For non-ordinary days a similar behavior can be found although in lesser magnitude. Taking this into account, the smooth curve of the squared pseudo residuals satisfactorily represents the ...
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Trend analysis of CO2 and CH4 recorded at a semi-natural site in the northern plateau of the Iberian Peninsula
... beginning and end of the measurement period for this latter method could be attributed to a border effect, since calculations were made with half the observations in the window. The fl uctu- ating behaviour of the ...
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Análisis bayesiano de modelos lineales - bilineales.
... the linear effects (genotypes or ...the linear effects the usual normal hierarchical structure is utilized and priors for precisions are assumed to follow gamma ...
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An Introduction to Generalized Linear Models, Second Edition. Dobson
... logistic regression one ofthe measured or observed categorical variables is regarded as the response, and all other variables are ex- planatory ...logistic regression yield odds ratio estimates which are ...
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A literature review on the application of evolutionary computing to credit scoring
... that linear discriminant anal- ysis is superior to genetic algorithms and neural ...the linear discriminant analysis model is better than ge- netic algorithms and three other approaches to credit scoring, ...
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Near Infrared Spectroscopy for the Analysis of Macro and Micro Nutrients in Sugarcane Leaves
... error of prediction (SEP), and BIAS (difference between NIR predicted values and the values determined by the reference chemistry). The SEP is a true measure of the performance of the equation on unknown samples and is ...
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Reply to Roberto’s Steiner’s Comments on our Chapter
... Variables in logs. Low frequency movements calculated using a robust version of a local regression using weighted linear least squares and a 2nd degree polynomial model that assigns lower weight to outliers ...
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Design and development of a hate speech detector in social networks based on Deep Learning technologies
... In order to optimize the algorithm behaviour, the GridSearchCV tool provided by Scikit- learn has been used. This module allows you to know the hyper-parameters that give the best results to a classifier when classifying ...
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Aroma profile design of wine spirits: Multi objective optimization using response surface methodology
... In the case of fruity esters, their values were below their quantifi- cation limits in the last fractions, due to depletion over time. For this reason, the sum of squares regression did not fi nd linear signi ...
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Sangrado despus de tener hipotermia profunda y paro circulatorio en nios
... stepwise linear regression analysis in a series of 495 children indicated that platelet count (< 108,000/microL) and thromboelastography maximum amplitude (MA) during CPB were the variables most signifi ...
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SYLLABUS Statistics Applied to Education and Psychology doc
... Course is theoretical and practical, belongs to the area of science; it is designed to develop and expand the skills of analysis of educational data, psychological, and social data that you began to acquire in the course ...
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