1. Robust time series analysis- Provides various approaches for robust estimation of (partial) autocorrelation and autocovariance. There are also procedures for robust fitting and filtering of AR(p) processes as well as for robust change point detection.
Topic : Spatial Data & Statistics : Reading and Writing Spatial Data [Filter]
Topic : Time Series (Now Filtering)
Registered: 2011-08-10 11:10
3. Fitting RSLN models- Regime-switching lognormal (RSLN) models are prominently used in actuarial science and risk management. This package implements Bayesian methods to fit the model, enabling academics and practitioners to incorporate the RSLN model in their work.
4. pfda: Functional Principal Components- The PFDA package for R performs functional principal component analysis with B-splines for univariate and bivariate responses. Also handled are binary responses and an additive model for extra variables.
7. Sea Level Trends- The sealevel package provides utility functions to read data from sea level data archives such as PSMSL, CSIRO, Colorado.edu and Soest.
See http://publicwiki.deltares.nl/label/sealevel for examples.
9. RobKalman- Package robKalman implements several robustifications of rhe classical Kalman filter; a common filtering iterface for all robustifications is provided as well as S4-classes for state space models and filtering results.