Data analysis based on SISSREM: Shiny Interactive, Supervised and Systematic report from REpeated Measures data

SVMs applied to a regression problem perform a linear regression in the feature space using the -insensitive loss as cost function and, at the same time, regularizing the weights

Table 2 Results of general linear mixed models explaining variation in the minimum distance of approach of water pipit males exposed to song stimuli of varying frequency bandwidth of

Therefore, this study evaluated the predictive performance of regression models (Simple Linear Regres- sion [SLR], Multiple Linear Regression [MLR] and Generalized Additive

Then, § 3.2 deals with the linear and nonlinear size structured models for cell division presented in [13] and in [20, Chapter 4], as well as with the size structured model

To verify the nonlinear model, a simplified version for small oscillations is obtained and compared with other results [12-14] using reduced linear models for the triple

With respect to ±1-steganography, two new embedding methods based on perfect Z 2 Z 4 - linear codes are introduced, achieving a higher embedding rate for a given distortion

Experiments on simulated, financial and precipitation data are performed to compare SPAC with other methods for copula estimation, including parametric Student’s t and Gaussian

Tables 4–6 report the results of β-standardized coefficients for each variable for the two linear regression models comprising LAS traits and Murciano-Granadina zoometric