Comparing penalized splines and fractional polynomials for flexible modelling of the effects of continuous predictor variables

Computational Statistics and Data Analysis

Volumn 55, Issue 4, 2011, Pages 1540-1551

  Strasak, Alexander M ^a   Umlauf, Nikolaus ^b   Pfeiffer, Ruth M ^c   Lang, Stefan ^b  

^a INNSBRUCK MEDICAL UNIVERSITY   (Austria)

^b UNIVERSITY OF INNSBRUCK   (Austria)

^c NATIONAL CANCER INSTITUTE   (United States)

Author keywords

Generalized additive models; Simulation study; Smoothing

Indexed keywords

APPLIED RESEARCH; COMPARATIVE EVALUATIONS; DATA SETS; DEFAULT SETTING; EXTENSIVE SIMULATIONS; FRACTIONAL POLYNOMIALS; FUNCTIONAL FORMS; GENERALIZED ADDITIVE MODEL; GENERALIZED CROSS VALIDATION; MEAN SQUARED ERROR; NONLINEAR FUNCTIONS; P-SPLINES; PENALIZED SPLINES; PREDICTOR VARIABLES; RESTRICTED MAXIMUM LIKELIHOOD; SAMPLE SIZES; SIMULATION STUDIES; SMALL SAMPLE SIZE; SMOOTHING; SMOOTHING PARAMETER; SMOOTHING TECHNIQUES;

FUNCTIONS; MAXIMUM LIKELIHOOD; SIGNAL TO NOISE RATIO; SPLINES;

COMPUTER SIMULATION;

EID: 78650833529     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2010.10.019     Document Type: Article

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