A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
Abraham, A.& Steinberg, D. (2001). MARS: Still an alien planet in soft computing? Computational Science
Abraham, A. Sung, A.H. & Mukkamala, S. (2005). Intrusion detection using an ensemble of intelligent paradigms. Journal of Network and Computer Applications
Bacherer, N.E. Comiso, J.C. Gordon A.L. & Deveaux, R.D. (1993). Modeling of topographic effects on antarctic sea-ice using multivariate adaptive regression splines Journal of Geophysical Research-Oceans
Bennett, G.W. Abraham, B., & Chen, G.M. (1997). Parametric and non-parametric modelling of time series - An empirical study. Environmetrics
Chen, I.F. Shao, Y.E. Lee, T.S.& Chou, S.M. (2004). Mining the breast cancer pattern using artificial neural networks and multivariate adaptive regression splines. Expert Systems with Applications
Cooke, F. Huettmann, F.& Yen, P.P.W. (2004). A large-scale model for the at-sea distribution and abundance of Marbled Murrelets (Brachyramphus marmoratus) during the breeding season in coastal British Columbia, Canada. Ecological Modelling
Eaves, L.J. & York, T.P. (2001). Common disease analysis using multivariate adaptive regression splines (MARS): Genetic analysis workshop 12 simulated sequence data.  Genetic Epidemiology
Felicisimo, A.M.& Munoz, J. (2004). Comparison of statistical methods commonly used in predictive modelling. Journal of Vegetation Science
Frescino, T.S. & Moisen, G.C. (2002). Comparing five modelling techniques for predicting forest characteristics. Ecological Modelling
Guvenir, H.A. & Uysal, I. (1999). An overview of regression techniques for knowledge discovery. Knowledge Engineering Review
Heyden, Y.V. Massart, D.L. Xu, Q.S.& Put, R. (2004). Deferral of the rectal examination in blunt trauma patients: A clinical decision rule. Journal of Chromatography A
Janouch, M. Eerme, K. & Krzyscin, J.W. (2004). Long-term variations of the UV-B radiation over Central Europe as derived from the reconstructed UV time series. Annales Geophysicae
Johnson, E.L. Gunther, D. & Chen, V.C.P.  (2003). Solving for an optimal airline yield management policy via statistical learning. Journal of the Royal Statisical Society Series C-Applied Statistics
Kendler, K.S. Prescott, C.A. York, T.P. Kovalenko, P. & (2003). Fatigue in a community sample of twins. Psychological Medicine
Kim, S.H. Lacroix, R. Prasher, S.O.& Yang, C.C. (2004). Application of multivariate adaptive regression splines (Mars) to simulate soil temperature. Transactions of the ASAE
Kim, S.H. Lacroix, R. Prasher, S.O.& Yang, C.C. (2003). A multivariate adaptive regression splines model for simulation of pesticide transport in soils. Biosystems Engineering
Klinger, A. (2001). Inference in high dimensional generalized linear models based on soft thresholding. Journal of the Royal Statistical Society Series B-Statistical Methodology
Ko, M. & Osei-Bryson, K.M. (2004). Exploring the relationship between information technology investments and firm performance using regression splines analysis. Information & Management
Kowalski, B.R. & Sekulic, S. (1992). MARS-a tutorial. Journal of Chemometrics
Krzyscin, J.W. (2003). Nonlinear (MARS) modeling of long-term variations of surface UV-B radiation as revealed from the analysis of Belsk, Poland data for the period 1976-2000. Annales Geophysicae
Krzyscin, J.W. (2002). Long-term changes in ozone mini-hole event frequency over the Northern Hemisphere derived from ground-based measurements. International Journal of Climatology
Maitrepierre, L. Dewitte, B. & Fischer, M. (2004). A non-linear statistical downscaling model: El Nino/Southern oscillation impact on precipitation over New Caledonia. Geophysical Research Letters
Martius, C. (2003). Rainfall and air humidity: non-linear relationships with termite swarming in Amazonia. Anazoniana-Linmologia et Oecologia Regionalis Systemae Fluminis Amazonas
Massart, D.L. Janssen, P.A. Vinkers, H.M. Lewi, P.J. Koymans, L.M.H. Heeres, J. de Jonge, M.R. Daeyaert, F. Walczak, B. Daszykowski, M. & Xu, Q.S. (2004). Multivariate adaptive regression splines - studies of HIV reverse transcriptase inhibitors. Chemometrics and Intelligent Laboratory Systems
Maxion, R.A. Olszewski, R.T.& Banks, D.L. (2003). Comparing methods for multivariate nonparametric regression. Communications in Statistics-Simulation and Computation
McClure, R. Do, K.A. & Kuhnert, P.M. (2000). Combining non-parametric models with logistic regression: an application to motor vehicle injury data. Computational Statistics & Data Analysis
Meullenet, J.F. & Xiong, R. (2004). Application of Multivariate Adaptive Regression Splines (MARS) to the preference mapping of cheese sticks. Journal of Food Science
Nawaiseh, M. Mensah, S.& Attoh-Okine, N.O. (2003). Using multivariate adaptive regression splines (MARS) in pavement roughness prediction. Proceedings of the Institution of Civil Engineers-Transport
Olmeda, I.& Fernandez, E. (1995). Bankruptcy prediction with Artificial Neural Networks. From Natural to Artificial Neural Computation
Osei-Bryson, KM. & Ko, M. (2000). Using regression splines to assess the impact of information technology investments on productivity in the health care industry. Journal of Neurosurgery
Palmieri, S. & Finizio, M. (1998). Non-linear modelling of monthly mean vorticity time changes: an application to the western Mediterranean. Annales Geophysicae-Atmospheres Hydrospheres and Space Sciences
Ren, S.J. (2003). Modeling the toxicity of aromatic compounds to Tetrahymena pyriformis: The response surface methodology with nonlinear methods. Journal of Chemical Information and Computer Sciences
Ridker, P.M. Zee, R.Y.L. & Ccok, N.R. (2004). Tree and spline based association analysis of gene-gene interaction models for ischemic stroke. Statistics in Medicine
Rode, B.M. Schmidhammer, H. & Lahsen, J. (2001). Structure-activity relationship study of nonpeptide delta- opioid receptor ligands. Helvetica Chimica Acta
Rode, B.M. VanDang, G. & NguyenCong, V. (2004). Using multivariate adaptive regression splines to QSAR studies of dihydroartemisinin derivatives. European Journal of Medicinal Chemistry
Ryan, C.G. Friedman, J.H. Fisher, N.I.& Griffin, W.L. (1997). Statistical techniques for the classification of chromites in diamond exploration samples. Journal of Geochemical Expolration
Segal, M.R. & Keles, S. (2002). Residual-based tree-structured survival analysis. Statistics in Medicine
Sharman, R. Brown, B.G. Nychka, D.& Tebaldi, C. (2002). Flexible discriminant techniques for forecasting clear-air turbulence. Environmetrics
Shoemaker, C.A., Ruppert, D. & Chen, V.C.P. (1999). Applying experimental design and regression splines to high- dimensional continuous-state stochastic dynamic programming. Operations Research
Stevens, J.G. & Lewis, P.A.W. (1991). Nonlinear modeling of time-series using multivariate adaptive regression splines (MARS). Journal of American Statistical Association
Sung, A.H. & Mukkamala, S. (2004). Computational intelligent techniques for detecting denial of service attacks. Innovations in Applied Artificial Intelligence
Thomas, G. & Porcher, R. (2003). Order determination in nonlinear time series by penalized least-squares. Communications in Statistics-Simulation and Computation
Thomas, JP. Abraham, A.& Chebrolu, S. (1995). Hybrid feature selection for modeling intrusion detection systems. Neural Information Processing
Trier, A. Perez, P. & Silva, C. (2001). Statistical modelling and prediction of atmospheric pollution by particulate material: two nonparametric approaches. Environmetrics
Vollei, F., Freimut, B. & Briand, L.C. (2004). Using multiple adaptive regression splines to support decision making in code inspections. Journal of Sytems and Software
Walsh, M.G. & Shepherd, K.D. (2002). Development of reflectance spectral libraries for characterization of soil properties. Soil Science Society of America Journal
Wang, X.L., Zhang, X.B., & Cortereal, J. (1995). Downscaling GCM information to regional scales: A nonparametric multivariate regression approach. Climate Dynamics
Wust, J. Melo, W.L.& Briand, L.C. (2002). Assessing the applicability of fault-proneness models across object-oriented software projects. IEEE Transactions on Software Engineering
Yang, C.C. Prasher, S.O. Lacroix, R. Kim, S.H. (2004). Application of multivariate adaptive regression splines (Mars) to simulate soil temperature. Transactions of the ASAE
Yang, C.C. Prasher, S.O. Lacroix, R. Kim, S.H. (2003). A multivariate adaptive regression splines model for simulation of pesticide transport in soils. Biosystems Engineering
Yee, S.S. & Carey, W.P. (1992). Calibration of nonlinear solid-state sensor arrays using multivariate regression techniques. Sensors and Actuators B-Chemical
Zhang, H.P. (1997). Multivariate adaptive splines for analysis of longitudinal data. Journal of Computational and Graphical Statistics

