factor performs a Factor Analysis for x (principal component, principal axes). For each method you can interactively between two different criteria for the factors. At the end you get a draftman plot of the the chosen factors.
fastint estimates the additive components and their derivatives of an additive model using a modification of the integration estimator plus a one step backfit, see Kim, Linton and Hengartner (1997) and Linton (1996)
computes sequentially all possible CPC and CPCp models: Beginning with the proportional model, it steps down to the full CPC model and estimates subsequently all possible CPCp models. Additionally to Chi-Square-Statistics, it provides the Akaike (AIC) and Schwarz (SIC) Information Criteria for mode
Calculates the coefficient in applying a basis expansion by using Fourier series. In this case, it is assumed that the data unit can be expressed by a linear combination of finite terms of sine and cosine functions.
fwt2 is designed for 2-dimensional wavelet transformation. It corresponds mainly to dwt for the one-dimensional case. If needed it can work with the tensor product of one dimensional wavelet transforms.
Generates the translation invariant estimate of x with automatic hardthresholding. It is well-known that nonlinear wavelet estimators are not translation-invariant: if we shift the underlying data set by a small amount, apply nonlinear thresholding and shift the estimator back, then we usually obta