Search Results - subject:"kernel function"

Gaussian relevance vector MapReduce-based annealed Glowworm optimization for big medical data scheduling

Patan, Rizwan; Kallam, Suresh; Gandomi, Amir H.; Hanne, … - In: Journal of the Operational Research Society 73 (2022) 10, pp. 2204-2215

Persistent link: https://www.econbiz.de/10013532432

Bankruptcy prediction and stress quantification using support vector machine: Evidence from Indian banks

Shrivastava, Santosh Kumar; Ramudu, P. Janaki - In: Risks 8 (2020) 2, pp. 1-22

Banks play a vital role in strengthening the financial system of a country; hence, their survival is decisive for the stability of national economies. Therefore, analyzing the survival probability of the banks is an essential and continuing research activity. However, the current literature...

Persistent link: https://www.econbiz.de/10013200586

Bankruptcy prediction and stress quantification using support vector machine : evidence from Indian banks

Shrivastava, Santosh Kumar; Ramudu, P. Janaki - In: Risks : open access journal 8 (2020) 2/52, pp. 1-22

Persistent link: https://www.econbiz.de/10012292870

Kernel block bootstrap

Parente, Paulo M. D. C.; Smith, Richard J. - 2018

This article introduces and investigates the properties of a new bootstrap method for time-series data, the kernel block bootstrap. The bootstrap method, although akin to, offers an improvement over the tapered block bootstrap of Paparoditis and Politis (2001), admitting kernels with unbounded...

Persistent link: https://www.econbiz.de/10011941512

Kernel block bootstrap

Parente, Paulo M. D. C.; Smith, Richard J. - 2018 - This draft: July 2018

Persistent link: https://www.econbiz.de/10011878210

Heteroscedasticity and autocorrelation robust F and t tests in stata

Ye, Xiaoqing; Sun, Yixiao - 2018

Persistent link: https://www.econbiz.de/10011914436

Alternative Strategies in Learning Nonlinear Soft Margin Support Vector Machines

COCIANU, Catalina; STATE, Luminita; USCATU, Cristian - In: Informatica Economica 18 (2014) 2, pp. 42-52

The aims of the paper are multifold, to propose a new method to determine a suitable value of the bias corresponding to the soft margin SVM classifier and to experimentally evaluate the quality of the found value against one of the standard expression of the bias computed in terms of the support...

Persistent link: https://www.econbiz.de/10011165701

Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix

Lee, Wei-Ming; Kuan, Chung-Ming; Hsu, Yu-Chin - Institute of Economics, Academia Sinica - 2014

This paper extends Kiefer, Vogelsang, and Bunzel (2000) and Kiefer and Vogelsang (2002b) to propose a class of over-identifying restrictions (OIR) tests that are robust to heteroskedasticity and serial correlations of unknown form. These OIR tests do not require consistent estimation of the...

Persistent link: https://www.econbiz.de/10010739165

Testing over : identifying restrictions without consistent estimation of the asymptotic covariance matrix

Lee, Wei-ming; Kuan, Chung-ming; Hsu, Yu-Chin - 2014

Persistent link: https://www.econbiz.de/10010246721

Ethnic segregation and heterogeneous preferences of homeowners for housing and neighbourhood characteristics. Evidence from the Netherlands

Ong, Cheng Boon; De Witte, Kristof - United Nations University-Maastricht Economic Research … - 2013

This paper examines ethnically differentiated preferences for neighbourhood ethnic composition among homeowners in the Netherlands. Borrowing from price hedonic theory, it tests a fully nonparametric empirical model of housing choice. We exploit rich neighbourhood-level administrative data...

Persistent link: https://www.econbiz.de/10010856404