Results 181 to 190 of about 1,373,260 (211)

Accuracy in Parameter Estimation for the Root Mean Square Error of Approximation: Sample Size Planning for Narrow Confidence Intervals

Multivariate Behavioral Research, 2011
Ken Kelley, K. Lai
semanticscholar   +3 more sources

Effects of Multivariate Non-Normality and Missing Data on the Root Mean Square Error of Approximation

Structural Equation Modeling: A Multidisciplinary Journal, 2021
The root mean square error of approximation (RMSEA) with various corrections for non-normality is a common fit index in structural equation modeling (SEM).
Lisa J. Jobst, C. Heine, Max Auerswald, Morten Moshagen   +3 more
semanticscholar   +1 more source

Generative adversarial network (GAN) and enhanced root mean square error (ERMSE): deep learning for stock price movement prediction

Multimedia tools and applications, 2021
The prediction of stock price movement direction is significant in financial circles and academic. Stock price contains complex, incomplete, and fuzzy information which makes it an extremely difficult task to predict its development trend. Predicting and
Ashish Kumar, A. Alsadoon, P. Prasad, S. Abdullah, Tarik A. Rashid, Duong Thu Hang Pham, T. Nguyen   +6 more
semanticscholar   +1 more source

Improving the Root Mean Square Error of Approximation for Nonnormal Conditions in Structural Equation Modeling

Journal of Experimental Education, 2000
J. Nevitt, G. Hancock
semanticscholar   +3 more sources

Estimating the uncertainty in estimates of root mean square error of prediction: application to determining the size of an adequate test set in multivariate calibration

Chemometrics and Intelligent Laboratory Systems, 1999
N. Faber
semanticscholar   +3 more sources

On the root mean square error (RMSE) calculation for parameter estimation of photovoltaic models: A novel exact analytical solution based on Lambert W function

, 2020
In the literature, one can find a lot of methods and techniques employed to estimate single diode solar photovoltaic (PV) cell parameters. The efficiency of these methods is usually tested by calculating the Root Mean Square Error (RMSE) between the ...
Martin P. Ćalasan, S. Aleem, A. Zobaa
semanticscholar   +1 more source

Estimating the Maximum Likelihood Root Mean Square Error of Approximation (RMSEA) with Non-normal Data: A Monte-Carlo Study

Structural Equation Modeling: A Multidisciplinary Journal, 2020
Recent research has provided formulae for estimating the maximum likelihood (ML) RMSEA when mean or mean and variance, corrections for non-normality are applied to the likelihood ratio test statistic.
Chuanji Gao, Dexin Shi, Albert Maydeu-Olivares   +2 more
semanticscholar   +1 more source

Automatic Gamma Correction Based on Root-Mean-Square-Error Maximization

2020 International Conference on Computing and Information Technology (ICCIT-1441), 2020
Gamma correction is a well-known method used often for image enhancement, mainly to improve the luminance levels of dark and bright images. However, the enhancement level is highly affected by the gamma parameter used. In this paper, we propose a new iterative algorithm for automating the selection of the gamma value γ by maximizing the mean error ...
Ahmad S. Tarawneh, Ahmad B. Hassanat, Issam Elkhadiri, Dmitry Chetverikov, Khalid Almohammadi   +4 more
openaire   +1 more source

Normal-eye Zernike coefficients and root-mean-square wavefront errors

Journal of Cataract and Refractive Surgery, 2006
To compare aberrometry measurements from multiple sites and compute mean Zernike coefficients and root-mean-square (RMS) values for the entire data pool to serve as a reference set for normal, healthy adult eyes.Northeastern State University, Tahlequah, Oklahoma, USA.Data were collected from 10 laboratories that measured higher-order aberrations (HOAs)
Thomas O, Salmon, Corina, van de Pol
openaire   +2 more sources

A root-mean-square-error analysis of two-peak Gaussian and Lorentzian fittings of thin-film carbon Raman spectral data

Journal of Applied Physics, 2019
We perform two-Gaussian and two-Lorentzian peak fits for Raman spectral data corresponding to samples of thin-film carbon found in the scientific literature.
J. Laumer, S. O’Leary
semanticscholar   +1 more source