Filaments of crime: Informing policing via thresholded ridge estimation

Based on non-precision observation, it researches the inversion problem with morbid equality constraints. And according to the pathological problems exist for the coefficient matrix and the constraint matrix, and it suggests the ridge estimation of the double-k type derived Ridge to determine these parameters. The results show that a variety of programs and double k ridge estimate not only removes the constraint matrix morbid adverse effects, but also can better overcome the master model morbidity and constraint matrix caused by the presence of instability, which is a good estimate.

Download Full-text

On nonparametric ridge estimation for multivariate long-memory processes

Lithuanian Mathematical Journal ◽

10.1007/s10986-020-09480-y ◽

2020 ◽

Vol 60 (3) ◽

pp. 291-314 ◽

Cited By ~ 1

Author(s):

Jan Beran ◽

Klaus Telkmann

Keyword(s):

Long Memory ◽

Memory Processes ◽

Ridge Estimation ◽

Long Memory Processes

Download Full-text

Intuitionistic Fuzzy Partial Logistic Regression Model Using Ridge Methodology

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488520500221 ◽

2020 ◽

Vol 28 (04) ◽

pp. 527-543

Author(s):

Gholamreza Hesamian ◽

Mohammad Ghasem Akbari ◽

Mehdi Roozbeh

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Smooth Function ◽

Potential Application ◽

Goodness Of Fit ◽

Logistic Regression Model ◽

Numerical Examples ◽

Ridge Estimation ◽

Intuitionistic Fuzzy

This paper applies a ridge estimation approach in an existing partial logistic regression model with exact predictors, intuitionistic fuzzy responses, intuitionistic fuzzy coefficients and intuitionistic fuzzy smooth function to improve an existing intuitionistic fuzzy partial logistic regression model in the presence of multicollinearity. For this purpose, ridge methodology is also involved to estimate the parametric intuitionistic fuzzy coefficients and nonparametric intuitionistic fuzzy smooth function. Some common goodness-of-fit criteria are also used to examine the performance of the proposed regression model. The potential application of the proposed method are illustrated and compared with the intuitionistic partial logistic regression model through two numerical examples. The results clearly indicate the proposed ridge method is quite efficient in model’s performances when there is multicollinearity among the predictors.

Download Full-text