Medizinische Universität Graz - Research portal
Selected Publication:
SCHIMEK, MG; SCHMARANZ, KG.
DEPENDENT ERROR REGRESSION SMOOTHING - A NEW METHOD AND PC PROGRAM
COMPUT STAT DATA ANAL. 1994; 17(4): 457-464.
Doi: 10.1016/0167-9473(94)90024-8
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- Leading authors Med Uni Graz
- Schimek Michael
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- Abstract:
- The problem of cubic spline smoothing of dependent data like time series and growth curves is addressed in this paper. Available statistical systems like S-PLUS (STATISTICAL SCIENCES, INC., 1991) and XploRe (XploRe SYSTEMS, 1992) do not provide appropriate algorithms. We propose a simple penalized least squares method with a number of computational advantages. It is called Dependent Error Regression Smoothing (abb. DERS) and implemented in a PC program under MS-Windows of the same name. The implementation comprises two techniques in an exploratory setting for smoothing parameter choice when the errors are serially correlated.
- Find related publications in this database (Keywords)
- NONPARAMETRIC REGRESSION
- BAND-LIMITED MATRIX
- C++
- CUBIC SMOOTHING SPLINES
- CROSS-VALIDATION
- DEPENDENT ERRORS
- HAT MATRIX
- MEMORY MANAGEMENT
- PC IMPLEMENTATION
- RESIDUALS
- SERIAL CORRELATION
- SMOOTHING PARAMETER
- TIME SERIES
- TRIANGULAR MATRIX
- VARIANCE ESTIMATION
- AUTOREGRESSIVE
- MOVING AVERAGE
- MS-WINDOWS