The goal of this paper is to analyze the effect of OTC-DVP (over the counter delivery versus payment) fixed income market introduction in Slovenia on the term structure estimation and on the volatility of zero coupon yields and forward interest rates. For the purpose of the analysis Slovenian zero coupon and forward curves were estimated. The model used for yield curve estimation was Nelson-Sie...

M-type smoothing splines are a broad class of spline estimators that include the popular least-squares but also less susceptible to outlying observations and model misspecification. However, available asymptotic theory only covers based on smooth objective functions consequently leaves out frequently used resistant such as quantile Huber-type splines. We provide general treatment in this paper ...

We present an error analysis for the numerical diierentiation of noisy data via smoothing cubic splines. Our treatment is elementary enough to be included in a course on numerical analysis. Still, it accounts for all numerical problems that arise in the solution of much more complex ill-posed inverse problems.

This paper concerns the construction of a discontinuous parametric curve or surface from a finite set of points and tangent conditions. The method is adapted from the theory of the discrete smoothing variational splines to introduce a discontinuity set and some tangent conditions. Such method is justified by a convergence result.

We consider an efficient approximation of Bühlmann & Yu’s L2Boosting algorithm with component-wise smoothing splines. Smoothing spline base-learners are replaced by P-spline base-learners which yield similar prediction errors but are more advantageous from a computational point of view. In particular, we give a detailed analysis on the effect of various P-spline hyper-parameters on the boosting...

| A critical component of spline smoothing is the choice of knots, especially for curves with varying shapes and frequencies in its domain. We consider a two-stage knot selection scheme for adaptively tting splines to data subject to noise. A potential set of knots is chosen based on information from certain wavelet decompositions with the intention to place more points where the curve shows ra...

We propose a method for analyzing data which consist of curves on multiple individuals, i.e., longitudinal or functional data. We use a Bayesian model where curves are expressed as linear combinations of B-splines with random coefficients. The curves are estimated as posterior means obtained via Markov chain Monte Carlo (MCMC) methods, which automatically select the local level of smoothing. Th...

The focus of this paper is using nonparametric transfer function models in forecasting. Nonparametric smoothing methods are used to model the relationship between variables (the transfer function) and the noise is modeled as an Autoregressive Moving Average (ARMA) process. The transfer function is estimated jointly with the ARMA parameters. Nonparametric smoothing methods are flexible thus can ...

This paper demonstrates the use of smoothing spline ANOVA and T tests to analyze whether the influence of syllable final consonants on the preceding vowel differs for articulation and acoustics. The onset of vowels either followed by phrase-final /r/ or by phrase-initial /r/ is compared for two Scottish English speakers. To measure articulatory differences of opposing vowel pairs, smoothing spl...