Abstract

Analysis of variance type models are considered for a regression function or for the logarithm of a probability function, conditional probability function, density function, conditional density function, hazard function, conditional hazard function or spectral density function. Polynomial splines are used to model the main effects, and their tensor products are used to model any interaction components that are included. In the special context of survival analysis, the baseline hazard function is modeled and nonproportionality is allowed. In general, the theory involves the $L_2$ rate of convergence for the fitted model and its components. The methodology involves least squares and maximum likelihood estimation, stepwise addition of basis functions using Rao statistics, stepwise deletion using Wald statistics and model selection using the Bayesian information criterion, cross-validation or an independent test set. Publicly available software, written in C and interfaced to S/S-PLUS, is used to apply this methodology to real data.

Keywords

MathematicsWald testApplied mathematicsStatisticsModel selectionPolynomialPolynomial regressionBayesian information criterionFunction (biology)Variance functionRegression analysisStatistical hypothesis testingMathematical analysis

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Publication Info

Year
1997
Type
article
Volume
25
Issue
4
Citations
399
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Charles J. Stone, Mark Hansen, Charles Kooperberg et al. (1997). Polynomial splines and their tensor products in extended linear modeling: 1994 Wald memorial lecture. The Annals of Statistics , 25 (4) . https://doi.org/10.1214/aos/1031594728

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DOI
10.1214/aos/1031594728