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Estimating multiplicative and additive hazard functions by kernel methods

Linton, Oliver; Perch Nielsen, Jens; van de Geer, Sara - London School of Economics (LSE) - 2001

We propose new procedures for estimating the univariate quantities of interest in both additive and multiplicative nonparametric marker dependent hazard models. We work with a full counting process framework that allows for left truncation and right censoring. Our procedures are based on kernels...

Persistent link: https://www.econbiz.de/10010745292

Estimating Multiplicative and Additive Hazard Functions by Kernel Methods

Linton, Oliver; Nielsen, Jens Perch; Geer, Sara van de - Suntory and Toyota International Centres for Economics … - 2001

Persistent link: https://www.econbiz.de/10005797514

R robustified additive nonparametric regression

Tamine, Julien; Härdle, Wolfgang; Yang, Lijian - 2002

asymptotic distribution, we also obtain robustness results for our estimator. All of our results are valid for a broad class of ß …

Persistent link: https://www.econbiz.de/10010310510

R robustified additive nonparametric regression

Tamine, Julien; Härdle, Wolfgang; Yang, Lijian - Sonderforschungsbereich 373, Quantifikation und … - 2002

asymptotic distribution, we also obtain robustness results for our estimator. All of our results are valid for a broad class of ß …

Persistent link: https://www.econbiz.de/10010983510

Support vector machines with evolutionary feature selection for default prediction

Härdle, Wolfgang Karl; Prastyo, Dedy Dwi; Hafner, Christian - 2012

banks in order to measure their client's degree of risk, and for firms to operate successfully. The SVM with evolutionary … and probit models as benchmark On overall, GA-SVM is outperforms compared to the benchmark models in both training and …

Persistent link: https://www.econbiz.de/10010318756

Forecasting corporate distress in the Asian and Pacific region

Moro, Russ; Härdle, Wolfgang Karl; Aliakbari, Saeideh; … - 2011

Support Vector Machine (SVM) and a logistic regression (Logit). Among different financial ratios suggested as predictors of … accuracy the SVM has a lower model risk than the Logit on average and displays a more robust performance. This result holds …

Persistent link: https://www.econbiz.de/10010281539

Estimation of cross-lingual news similarities using text-mining methods

Wang, Zhouhao; Liu, Enda; Sakaji, Hiroki; Ito, Tomoki; … - In: Journal of risk and financial management : JRFM 11 (2018) 1, pp. 1-13

In this research, two estimation algorithms for extracting cross-lingual news pairs based on machine learning from financial news articles have been proposed. Every second, innumerable text data, including all kinds news, reports, messages, reviews, comments, and tweets are generated on the...

Persistent link: https://www.econbiz.de/10011855132

Nowcasting GDP: what are the gains from machine learning algorithms?

Arro-Cannarsa, Milen; Scheufele, Rolf - 2024

Persistent link: https://www.econbiz.de/10015044842

On robustness properties of convex risk minimization methods for pattern recognition

Christmann, Andreas; Steinwart, Ingo - 2003

The paper brings together methods from two disciplines: machine learning theory and robust statistics. Robustness …. Kernel logistic regression, support vector machines, least squares and the AdaBoost loss function are treated as special …

Persistent link: https://www.econbiz.de/10010477496

On a strategy to develop robust and simple tariffs from motor vehicle insurance data

Christmann, Andreas - 2004

nonparametric approach based on a combination of kernel logistic regression and ¡support vector regression. …

Persistent link: https://www.econbiz.de/10010516923