Similar Search Results

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

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/10005797514

Estimating Multiplicative and Additive Hazard Functions by Kernel Methods.

Linton, Oliver B.; Perch Nielsen, Jens; Van de Geer, Sara - Ehrvervøkonomisk Institut, Institut for Økonomi - 2001

Persistent link: https://www.econbiz.de/10005802136

Estimating multiplicative and additive hazard functions by kernel methods

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

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

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

Predicting credit card customer churn in banks using data mining

Kumar, Dudyala Anil; Ravi, V. - In: International Journal of Data Analysis Techniques and … 1 (2008) 1, pp. 4-28

Forest (RF), Radial Basis Function (RBF) network and Support Vector Machine (SVM) as the constituents. The dataset was taken …

Persistent link: https://www.econbiz.de/10005753847

Predicting credit card customer churn in banks using data mining

Kumar, Dudyala Anil; Ravi, V. - In: International Journal of Data Analysis Techniques and … 1 (2008) 1, pp. 4-28

Forest (RF), Radial Basis Function (RBF) network and Support Vector Machine (SVM) as the constituents. The dataset was taken …

Persistent link: https://www.econbiz.de/10008563411

Atmospheric environment impact assessment of thermal power plant

Niu, Dongxiao; Wang, Weijun; Wu, Desheng - In: International Journal of Global Energy Issues 32 (2009) 4, pp. 361-371

taking the advantage of both SVM and BP networks and avoiding their defects. An actual instance addressed in the paper shows …

Persistent link: https://www.econbiz.de/10008755327

Does modeling lead to more accurate classification?: A study of relative efficiency in linear classification

Lee, Yoonkyung; Wang, Rui - In: Journal of Multivariate Analysis 133 (2015) C, pp. 232-250

discriminant analysis (LDA) under the normal setting, we contrast such algorithmic methods as the support vector machine (SVM) and … 60% for the SVM and 50% to 80% for boosting when compared to the LDA. However, a smooth variant of the SVM is shown to be … experiments under various settings for comparisons of finite-sample performance and robustness to mislabeling and model …

Persistent link: https://www.econbiz.de/10011116232

Asymptotics of SIMEX-based variance estimation

Fang, Yun; Zhu, Li-Xing - In: Metrika 75 (2012) 3, pp. 329-345

Persistent link: https://www.econbiz.de/10010539345

Specification Testing for Multivariate Time Series Volatility Models

Lee, Yoon-Jin; Hong, Yongmiao - Econometric Society - 2004

Volatility models have been playing an important role in economics and finance. Using a multivariate generalized spectral approach, we propose a new class of generally applicable omnibus tests for univariate and multivariate volatility models. Both GARCH models and stochastic volatility models...

Persistent link: https://www.econbiz.de/10005342373

1
2
3
4
5
6
7
8
9
10
Next
Last