Search results for " Regression"
showing 10 items of 1835 documents
Polynomial Fuzzy Models for Nonlinear Control: A Taylor Series Approach
2009
Classical Takagi-Sugeno (T-S) fuzzy models are formed by convex combinations of linear consequent local models. Such fuzzy models can be obtained from nonlinear first-principle equations by the well-known sector-nonlinearity modeling technique. This paper extends the sector-nonlinearity approach to the polynomial case. This way, generalized polynomial fuzzy models are obtained. The new class of models is polynomial, both in the membership functions and in the consequent models. Importantly, T-S models become a particular case of the proposed technique. Recent possibilities for stability analysis and controller synthesis are also discussed. A set of examples shows that polynomial modeling is…
Determination of thermometric parameters from the conductance curve of the normal metal based tunnel junction array
1997
Abstract We propose a method for extracting thermometric parameters from the measured conductance curve, against bias voltage, of a tunnel junction array. Instead of fitting the whole theoretical conductance curve to the experiment, we perform several polynomial fits to selected bias regions. The advantages of this method is that polynomial fits are linear in their fitting parameters whereas the theoretical form for the conductance is inherently nonlinear. This way the proposed method is about three orders of magnitude faster than the nonlinear fit. Optimizing this polynomial fit procedure is discussed.
Polynomial Regression and Measurement Error
2020
Many of the phenomena of interest in information systems (IS) research are nonlinear, and it has consequently been recognized that by applying linear statistical models (e.g., linear regression), we may ignore important aspects of these phenomena. To address this issue, IS researchers are increasingly applying nonlinear models to their datasets. One popular analytical technique for the modeling and analysis of nonlinear relationships is polynomial regression, which in its simplest form fits a "U-shaped" curve to the data. However, the use of polynomial regression can be problematic when the independent variables are contaminated with measurement error, and the implications of error can be m…
On the semi-automatic retrieval of biophysical parameters based on spectral index optimization
2014
Abstract: Regression models based on spectral indices are typically empirical formulae enabling the mapping of biophysical parameters derived from Earth Observation (EO) data. Due to its empirical nature, it remains nevertheless uncertain to what extent a selected regression model is the most appropriate one, until all band combinations and curve fitting functions are assessed. This paper describes the application of a Spectral Index (SI) assessment toolbox in the Automated Radiative Transfer Models Operator (ARTMO) package. ARTMO enables semi-automatic retrieval and mapping of biophysical parameters from optical remote sensing observations. The SI toolbox facilitates the assessment of biop…
A Machine Learning Model to Predict Intravenous Immunoglobulin-Resistant Kawasaki Disease Patients: A Retrospective Study Based on the Chongqing Popu…
2021
Objective: We explored the risk factors for intravenous immunoglobulin (IVIG) resistance in children with Kawasaki disease (KD) and constructed a prediction model based on machine learning algorithms.Methods: A retrospective study including 1,398 KD patients hospitalized in 7 affiliated hospitals of Chongqing Medical University from January 2015 to August 2020 was conducted. All patients were divided into IVIG-responsive and IVIG-resistant groups, which were randomly divided into training and validation sets. The independent risk factors were determined using logistic regression analysis. Logistic regression nomograms, support vector machine (SVM), XGBoost and LightGBM prediction models wer…
S77. JUMPING TO CONCLUSIONS AND FACIAL EMOTION RECOGNITION IMPAIRMENT IN FIRST EPISODE PSYCHOSIS ACROSS EUROPE
2018
Abstract Background Jumping to conclusions (JTC) is a well-established reasoning and data gathering bias found in patients with psychosis even at illness onset (First Episode Psychosis, FEP). Preliminary work in this field focused primarily on the association with delusions, although jumping to conclusions has also been found in non-deluded schizophrenia patients after remission, and in individual with at risk mental state. Moreover, psychotic patients tend to show impairments in social cognition, struggling in identifying, processing and interpreting social clues. Deficits in facial emotion recognition (FER) – a key component of the construct – represent a well-replicated finding in schizo…
Characterization of pre-treatments on wood chips prior to delignification by near infrared spectroscopy
2017
A near infrared (NIR) spectroscopy-based method for predicting yields and lignin contents of differently pre-treated silver/white birch (Betula pendula/B. pubescens) and Scots pine (Pinus sylvestris) chips was developed. The approach was to create multivariate calibration models from the NIR data by the partial least squares (PLS) method. Both parameters are important factors when adjusting adequate conditions for pre-treatments either with hot-water (HW) as such and slightly acidified HW (collectively referred to as autohydrolysis) or dilute alkaline aqueous solutions prior to alkaline pulping. Pre-treatment conditions were varied with respect to temperature (130 °C and 150 °C) and treatme…
The Somatic Symptom Disorder - B Criteria Scale (SSD-12): Factorial structure, validity and population-based norms.
2017
The Somatic Symptom Disorder - B Criteria Scale (SSD-12) assesses the psychological features of DSM-5 Somatic Symptom Disorder (SSD). The present study investigates the dimensionality and psychometric properties in a general population sample and provides norm values.Test dimensionality was evaluated via confirmatory factor analysis and nonparametric item response theory. Correlational analyses and logistic regression models based on related measures (SSS 8, PHQ-2, GAD-2, Health Care Utilization) were used to derive predictive validity. Age and gender specific norms were derived via quantile regression.The SSD-12 has good item characteristics and excellent reliability (Cronbach's α=0.95). C…
The Development of the Brief Eating Disorder in Athletes Questionnaire
2014
MARTINSEN, M., I. HOLME, A. M. PENSGAARD, M. K. TORSTVEIT, and J. SUNDGOT-BORGEN. The Development of the Brief Eating Disorder in Athletes Questionnaire. Med. Sci. Sports Exerc., Vol. 46, No. 8, pp. 1666–1675, 2014. Purpose: The objective of this study is to design and validate a brief questionnaire able to discriminate between female elite athletes with and without an eating disorder (ED). Methods: In phase I, 221 (89.5%) adolescent athletes participated in a screening including the Eating Disorder Inventory-2 (EDI2) and questions related to ED. All athletes reporting symptoms associated with ED (n = 96, 94.1%) and a random sample without symptoms (n = 88, 86.3%) attended the ED Examinatio…
Comparative evaluation of three semi-quantitative radiographic grading techniques for knee osteoarthritis in terms of validity and reproducibility in…
2008
OBJECTIVE: The objective of this work was to compare the measurement properties of three categorical X-ray scoring methods of knee osteoarthritis (OA), both on semiflexed and extended views. METHODS: In data obtained from trials and cohorts, X-rays were graded using Kellgren and Lawrence (KL), the OA Research Society International (OARSI) joint space narrowing score, and measurement of joint space width (JSW). JSW was analyzed as a categorical variable. Construct validity was assessed through logistic regression between X-ray stages and Western Ontario and McMaster Universities OA Index. Inter-observer reliability was assessed in 50 subjects for extended views by weighted kappa. Intra-obser…