Search
Search Results
-
Semiparametric proportional means model for marker data contingent on recurrent event
In many biomedical studies with recurrent events, some markers can only be measured when events happen. For example, medical cost attributed to...
-
The forward search: Theory and data analysis
The Forward Search is a powerful general method, incorporating flexible data-driven trimming, for the detection of outliers and unsuspected structure...
-
A comparison study of extreme precipitation from six different regional climate models via spatial hierarchical modeling
We analyze output from six regional climate models (RCMs) via a spatial Bayesian hierarchical model. The primary advantage of this approach is that...
-
A comparison of official population projections with Bayesian time series forecasts for England and Wales
We compare official population projections with Bayesian time series forecasts for England and Wales. The Bayesian approach allows the integration of...
-
Change-Point Problems: Bibliography and Review
Five types of change-point problems concerning change in mean, variance, slope, hazard rate, and space-time distribution are briefly reviewed and a...
-
Normal Distribution
In Chaps. 2 and 5 we occasionally referred to a normal distribution either informally (bell-shaped distributions/histograms) or formally, as in Sect....
-
Linear Systems Estimation
One of the most fundamental equations in this book is the solution to the Bayesian linear least-squares estimator of (3.114): 9.1...
-
A Spatio-Temporal Downscaler for Output From Numerical Models
Often, in environmental data collection, data arise from two sources: numerical models and monitoring networks. The first source provides predictions...
-
Predictive comparison of joint longitudinal-survival modeling: a case study illustrating competing approaches
The joint modeling of longitudinal and survival data has received extraordinary attention in the statistics literature recently, with models and...
-
Non-parametric Decoding on Discrete Time Series and Its Applications in Bioinformatics
We address the question: How do we non-parametrically decode the unknown state-space vector underlying a lengthy discrete time series? The time...
-
List of Supplementary Contributed and Invited Papers Only Available on springerlink.com
Clustering of Waveforms-Data Based on FPCA Direction Giada Adelfio, Marcello Chiodi, Antonino D’Alessandro, Dario Luzio
-
Interactivity
Interactivity is a fundamental property of items in the real world. We expect to be able to turn things on, move them around, change locations, or at...
-
On computational aspects of Bayesian spatial models: influence of the neighboring structure in the efficiency of MCMC algorithms
This study applies computationally intensive methods for Bayesian analysis of spatially distributed data. It is assumed that the space is divided in...
-
A model-free test for independence between time series
The problem of assessing the independence of time series arises in many situations, including evaluating the spatial synchrony of populations in...
-
Introduction to Seasonality
In this chapter we define what we mean by a season and show some methods for investigating and modelling a seasonal pattern. Three excellent, but...
-
Bayesian regularisation in structured additive regression: a unifying perspective on shrinkage, smoothing and predictor selection
This paper surveys various shrinkage, smoothing and selection priors from a unifying perspective and shows how to combine them for Bayesian...
-
Framework
This chapter lays the groundwork for the chapters to come. In it is described the basics of how a visualization is constructed, giving a rough...
-
Least squares and shrinkage estimation under bimonotonicity constraints
In this paper we describe active set type algorithms for minimization of a smooth function under general order constraints, an important case being...
-
Comparing sampling patterns for kriging the spatial mean temporal trend
In monitoring the environment one often wishes to detect the temporal trend in a variable that varies across a region. A useful executive summary is...
-
Approximating data
There are essentially two statistical paradigms, the Bayesian and frequentist. Despite their obvious differences the two approaches have certain...